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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
null |
School of ECEE, Arizona State University; Department of ECE, The Ohio State University; Department of ECE, University of California, Davis
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6873; None
| null | 0 | null | null | null |
2;3;2;3
| null |
Sen Lin, Jialin Wan, Tengyu Xu, Yingbin Liang, Junshan Zhang
|
https://iclr.cc/virtual/2022/poster/6873
|
offline reinforcement learning;model-based reinforcement learning;behavior policy;Meta-reinforcement learning
| null | 2.5 | null |
https://openreview.net/forum?id=EBn0uInJZWh
|
iclr
| 0.333333 | 0.333333 | null |
main
| 6.5 |
6;6;6;8
|
2;4;4;4
|
https://iclr.cc/virtual/2022/poster/6873
|
Model-Based Offline Meta-Reinforcement Learning with Regularization
| null | null | 3.5 | 3.75 |
Poster
|
3;4;4;4
|
2;3;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Adversarial Tranferability;Early stop;Adversarial Training;Non-robust Features
| null | 2.25 | null | null |
iclr
| -0.57735 | -0.57735 | null |
main
| 4 |
3;3;5;5
|
3;2;2;2
| null |
Early Stop And Adversarial Training Yield Better surrogate Model: Very Non-Robust Features Harm Adversarial Transferability
| null | null | 2.25 | 3.75 |
Withdraw
|
4;4;3;4
|
2;3;2;2
|
null |
School of Computer Science and Engineering, Sun Yat-sen University; School of Mathematical Sciences, Peking University; Key Lab. of Machine Perception (MoE), School of Artificial Intelligence, Peking University; Institute for Artificial Intelligence, Peking University
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6659; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Yifei Wang, Qi Zhang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
|
https://iclr.cc/virtual/2022/poster/6659
|
Contrastive Learning;Representation Learning;Self-supervised Learning
| null | 2.75 | null |
https://openreview.net/forum?id=ECvgmYVyeUz
|
iclr
| -0.57735 | 0 | null |
main
| 7 |
6;6;8;8
|
4;3;3;4
|
https://iclr.cc/virtual/2022/poster/6659
|
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap
|
https://github.com/zhangq327/ARC
| null | 3.5 | 3.75 |
Poster
|
4;4;4;3
|
2;3;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
Medical image diagnosis;Deep learning;Regularization strategy;Data augmentation
| null | 2.333333 | null | null |
iclr
| -0.944911 | 0.755929 | null |
main
| 4.666667 |
3;5;6
|
2;2;3
| null |
Look at here : Utilizing supervision to attend subtle key regions
| null | null | 2.333333 | 4.333333 |
Withdraw
|
5;4;4
|
2;2;3
|
null |
New York University
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/6095; None
| null | 0 | null | null | null |
3;4;3;3
| null |
Nate Gruver, Marc A Finzi, Samuel Stanton, Andrew Wilson
|
https://iclr.cc/virtual/2022/poster/6095
| null | null | 3.5 | null |
https://openreview.net/forum?id=EDeVYpT42oS
|
iclr
| -0.333333 | 0.333333 | null |
main
| 7.5 |
6;8;8;8
|
3;3;4;3
|
https://iclr.cc/virtual/2022/poster/6095
|
Deconstructing the Inductive Biases of Hamiltonian Neural Networks
| null | null | 3.25 | 3.75 |
Spotlight
|
4;4;4;3
|
3;4;4;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null |
Personalized federated learning;Meta-learning;Information theory
| null | 2.333333 | null | null |
iclr
| -0.188982 | 0.944911 | null |
main
| 4.666667 |
3;5;6
|
3;4;4
| null |
Towards Generalizable Personalized Federated Learning with Adaptive Local Adaptation
| null | null | 3.666667 | 3.666667 |
Reject
|
4;3;4
|
2;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;2;4
| null | null | null |
darts;differentiable;architecture;search;neural;nas;rl;reinforcement;learning;procgen;supernet;softmax;variable;ppo;rainbow;off-policy;on-policy;convolutional;autorl;automated;one-shot;efficient
| null | 2.5 | null | null |
iclr
| 0 | -0.942809 | null |
main
| 5 |
3;5;6;6
|
4;3;3;3
| null |
RL-DARTS: Differentiable Architecture Search for Reinforcement Learning
| null | null | 3.25 | 4 |
Reject
|
4;4;5;3
|
2;2;3;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;3;3
| null | null | null | null | null | 2.333333 | null | null |
iclr
| 0 | -0.5 | null |
main
| 4.333333 |
3;5;5
|
3;3;2
| null |
Privacy Auditing of Machine Learning using Membership Inference Attacks
|
https://github.com/privacytrustlab/ml_privacy_meter
| null | 2.666667 | 4 |
Reject
|
4;4;4
|
2;3;2
|
null | null |
2022
| 3.333333 | null | null | 0 | null | null | null |
3;3;4
| null | null | null |
Transformer;Pooling;Downsampling;Efficiency
| null | 2.666667 | null | null |
iclr
| 0 | 0.5 | null |
main
| 6 |
5;5;8
|
4;3;4
| null |
Token Pooling in Vision Transformers
| null | null | 3.666667 | 4 |
Reject
|
4;4;4
|
3;2;3
|
null |
McGill University; Google Brain; Mila, McGill University; Mila, McGill University, DeepMind
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6264; None
| null | 0 | null | null | null |
3;2;3;3
| null |
David Venuto, Elaine Lau, Doina Precup, Ofir Nachum
|
https://iclr.cc/virtual/2022/poster/6264
| null | null | 2.75 | null |
https://openreview.net/forum?id=EHaUTlm2eHg
|
iclr
| -0.333333 | 0.57735 | null |
main
| 6.5 |
6;6;6;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6264
|
Policy Gradients Incorporating the Future
| null | null | 3.5 | 3.5 |
Poster
|
3;5;3;3
|
3;2;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
time-series;meta-learning;closed-form;solvers
| null | 1.333333 | null | null |
iclr
| -0.5 | 0 | null |
main
| 3.666667 |
3;3;5
|
2;2;2
| null |
Meta-Forecasting by combining Global Deep Representations with Local Adaptation
| null | null | 2 | 3.333333 |
Reject
|
4;3;3
|
1;2;1
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;2;2;3
| null | null | null |
regular expression;program synthesis;programming by examples;deep learning;neural network
| null | 2.75 | null | null |
iclr
| -0.816497 | 0.816497 | null |
main
| 6 |
5;5;6;8
|
3;3;4;4
| null |
SplitRegex: Faster Regex Synthesis via Neural Example Splitting
| null | null | 3.5 | 3.5 |
Reject
|
4;4;3;3
|
2;2;3;4
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
3;1;3;2
| null | null | null | null | null | 2.25 | null | null |
iclr
| 0 | 0.57735 | null |
main
| 5.25 |
5;5;5;6
|
3;3;4;4
| null |
A new look at fairness in stochastic multi-armed bandit problems
| null | null | 3.5 | 4 |
Reject
|
4;4;4;4
|
2;2;3;2
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3;3
| null | null | null |
neural network dynamics;time-evolving graphs;interpretation of neural networks;performance prediction
| null | 2.5 | null | null |
iclr
| -0.800641 | 0.919866 | null |
main
| 5.5 |
3;5;6;8
|
2;3;4;4
| null |
Convolutional Neural Network Dynamics: A Graph Perspective
| null | null | 3.25 | 3.5 |
Reject
|
5;3;3;3
|
2;3;2;3
|
null |
University of Cambridge; Google Brain Robotics; The Alan Turing Institute; Columbia University
|
2022
| 3.333333 |
https://iclr.cc/virtual/2022/poster/6410; None
| null | 0 | null | null | null |
3;3;4
| null |
Krzysztof Choromanski, Han Lin, Haoxian Chen, Arijit Sehanobish, Yuanzhe Ma, Deepali Jain, Jake Varley, Andy Zeng, Michael Ryoo, Valerii Likhosherstov, Dmitry Kalashnikov, Vikas Sindhwani, Adrian Weller
|
https://iclr.cc/virtual/2022/poster/6410
|
random features;softmax kernel;attention mechanism;compositional kernels
| null | 2.666667 | null |
https://openreview.net/forum?id=EMigfE6ZeS
|
iclr
| 0.5 | 0.5 | null |
main
| 7.333333 |
6;8;8
|
3;3;4
|
https://iclr.cc/virtual/2022/poster/6410
|
Hybrid Random Features
| null | null | 3.333333 | 4.333333 |
Poster
|
4;5;4
|
3;3;2
|
null |
Department of Mathematics, University of Manchester, Manchester M13 9PL, UK; Department of Mathematics, UC Davis, Davis, CA 95616, USA; Department of Mathematics and Scientific Computing and Imaging (SCI) Institute, University of Utah, Salt Lake City, UT, 84102, USA; Department of Mathematics, UCLA, Los Angeles, CA, 90095, USA
|
2022
| 2.6 |
https://iclr.cc/virtual/2022/poster/7172; None
| null | 0 | null | null | null |
3;3;2;2;3
| null |
Matthew Thorpe, Tan M Nguyen, Hedi Xia, Thomas Strohmer, Andrea Bertozzi, Stanley J Osher, Bao Wang
|
https://iclr.cc/virtual/2022/poster/7172
|
graph deep learning;low-labeling rates;diffusion on graphs;random walk
| null | 1.6 | null |
https://openreview.net/forum?id=EMxu-dzvJk
|
iclr
| -0.408248 | 0.612372 | null |
main
| 6.4 |
6;6;6;6;8
|
4;3;3;3;4
|
https://iclr.cc/virtual/2022/poster/7172
|
GRAND++: Graph Neural Diffusion with A Source Term
| null | null | 3.4 | 3.4 |
Poster
|
4;4;3;3;3
|
2;2;2;2;0
|
null |
Under double-blind review
|
2022
| 0 | null | null | 0 | null | null | null | null | null |
Marwan Omar
| null |
Adversarial training;NLP models;NLP robustness;adversarial attacks.
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 0 | null | null | null |
Adversarial Training: A simple and efficient technique to Improving NLP Robustness
| null | null | 0 | 0 |
Withdraw
| null | null |
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null | null | null | 2.333333 | null | null |
iclr
| 0.5 | 1 | null |
main
| 4.333333 |
3;5;5
|
2;3;3
| null |
Testing-Time Adaptation through Online Normalization Estimation
| null | null | 2.666667 | 4.333333 |
Withdraw
|
4;5;4
|
2;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2;2
| null | null | null |
quantum neural networks;variational quantum circuits;end-to-end learning framework;tensor-train network
| null | 1.8 | null | null |
iclr
| 0.166667 | 0.612372 | null |
main
| 4.2 |
3;3;5;5;5
|
3;2;3;3;3
| null |
QTN-VQC: An End-to-End Learning Framework for Quantum Neural Networks
| null | null | 2.8 | 3.6 |
Reject
|
3;4;3;4;4
|
2;1;2;2;2
|
null | null |
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/7181; None
| null | 0 | null | null | null |
1;3;3;4
| null |
Nikhil Ghosh, Song Mei, Bin Yu
|
https://iclr.cc/virtual/2022/poster/7181
|
training dynamics;kernels;SGD;deep bootstrap;gradient flow;random features;high-dimensional asymptotics;random matrix theory
| null | 2.25 | null |
https://openreview.net/forum?id=EQmAP4F859
|
iclr
| 0.894737 | 0.662266 | null |
main
| 6.25 |
5;6;6;8
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/7181
|
The Three Stages of Learning Dynamics in High-dimensional Kernel Methods
| null | null | 3.75 | 3.75 |
Poster
|
2;4;4;5
|
2;0;3;4
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;2;3;4
| null | null | null |
Latent Variable Models;Bayesian Methods;Variational Inference;Graph Neural Networks
| null | 2 | null | null |
iclr
| -0.773545 | 0.863868 | null |
main
| 4.75 |
3;3;5;8
|
2;3;3;4
| null |
Edge Partition Modulated Graph Convolutional Networks
| null | null | 3 | 3.75 |
Reject
|
5;4;3;3
|
2;0;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;2;2;3
| null | null | null |
graph neural network;link prediction;virtual node
| null | 2.75 | null | null |
iclr
| -0.333333 | -0.333333 | null |
main
| 5.75 |
5;6;6;6
|
4;4;3;4
| null |
Revisiting Virtual Nodes in Graph Neural Networks for Link Prediction
| null | null | 3.75 | 3.75 |
Reject
|
4;4;4;3
|
2;2;3;4
|
null |
Department of Electrical and Computer Engineering, Texas A&M University; Department of Electrical and Computer Engineering, University of Texas at Austin; Department of Electrical and Computer Engineering, Texas A&M University and Department of Computer Science and Engineering, Texas A&M University
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6796; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Yuning You, Yue Cao, Tianlong Chen, Zhangyang Wang, Yang Shen
|
https://iclr.cc/virtual/2022/poster/6796
| null | null | 2.5 | null |
https://openreview.net/forum?id=EVVadRFRgL7
|
iclr
| 1 | 0.57735 | null |
main
| 5.5 |
5;5;6;6
|
2;3;3;3
|
https://iclr.cc/virtual/2022/poster/6796
|
Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How
|
https://github.com/Shen-Lab/Bayesian-L2O
| null | 2.75 | 3.5 |
Poster
|
3;3;4;4
|
2;3;3;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Question Answering;Natural Language Processing;Attention Methods
| null | 2 | null | null |
iclr
| -0.57735 | 0 | null |
main
| 4.5 |
3;5;5;5
|
2;2;2;2
| null |
Iterative Hierarchical Attention for Answering Complex Questions over Long Documents
| null | null | 2 | 3.5 |
Reject
|
4;3;4;3
|
2;2;2;2
|
null |
Stanford University; NVIDIA; NVIDIA, California Institute of Technology
|
2022
| 2.666667 |
https://iclr.cc/virtual/2022/poster/6073; None
| null | 0 | null | null | null |
3;2;3
| null |
John Guibas, Morteza Mardani, Zongyi Li, Andrew Tao, Anima Anandkumar, Bryan Catanzaro
|
https://iclr.cc/virtual/2022/poster/6073
|
self attention;linear complexity;high-resolution inputs;operator learning;Fourier transform
| null | 2.666667 | null |
https://openreview.net/forum?id=EXHG-A3jlM
|
iclr
| -1 | 0.188982 | null |
main
| 6.666667 |
6;6;8
|
4;1;3
|
https://iclr.cc/virtual/2022/poster/6073
|
Efficient Token Mixing for Transformers via Adaptive Fourier Neural Operators
|
github.com/jtguibas/AdaptiveFourierNeuralOperator
| null | 2.666667 | 3.666667 |
Poster
|
4;4;3
|
4;2;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
Adversarial training;Data quality;Robust overfitting;Robustness overestimation;Robustness-accuracy trade-off
| null | 2.75 | null | null |
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
3;3;4;3
| null |
Data Quality Matters For Adversarial Training: An Empirical Study
| null | null | 3.25 | 4 |
Reject
|
4;4;5;3
|
4;2;3;2
|
null | null |
2022
| 2.4 | null | null | 0 | null | null | null |
2;3;3;1;3
| null | null | null |
weight initialization;deep residual network;deterministic initialization;optimization
| null | 2.4 | null | null |
iclr
| -0.408248 | 0.534522 | null |
main
| 5.2 |
5;5;5;5;6
|
4;2;3;3;4
| null |
ZerO Initialization: Initializing Residual Networks with only Zeros and Ones
| null | null | 3.2 | 3.4 |
Reject
|
3;3;4;4;3
|
2;3;2;2;3
|
null |
CDRIN, Matane, Canada; Mila Quebec AI Institute, Montreal, Canada and Universite de Montreal, Montreal, Canada; Columbia University, New York City, USA
|
2022
| 2.333333 |
https://iclr.cc/virtual/2022/poster/6224; None
| null | 0 | null | null | null |
2;2;3
| null |
Victor Schmidt, Alexandra Luccioni, Mélisande Teng, Tianyu Zhang, Alexia Reynaud, Sunand Raghupathi, Gautier Cosne, Adrien Juraver, Vahe Vardanyan, Alex Hernandez-Garcia, Yoshua Bengio
|
https://iclr.cc/virtual/2022/poster/6224
|
GAN;Climate Change;Domain Adaptation;Representation Learning;Computer Vision;Application
| null | 2 | null |
https://openreview.net/forum?id=EZNOb_uNpJk
|
iclr
| 0 | 1 |
https://thisclimatedoesnotexist.com
|
main
| 5.333333 |
5;5;6
|
3;3;4
|
https://iclr.cc/virtual/2022/poster/6224
|
ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods
| null | null | 3.333333 | 4 |
Poster
|
4;4;4
|
2;2;2
|
null |
Institute for AI, Peking University & BIGAI; University of Oxford, Huawei R&D UK; University College London; ShanghaiTech University; Shanghai Jiao Tong University
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6244; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Jakub Grudzien Kuba, Ruiqing Chen, Muning Wen, Ying Wen, Fanglei Sun, Jun Wang, Yaodong Yang
|
https://iclr.cc/virtual/2022/poster/6244
|
Multi-Agent Reinforcement Learning;trust-region method;policy gradient method
| null | 3 | null |
https://openreview.net/forum?id=EcGGFkNTxdJ
|
iclr
| 0.57735 | -0.333333 | null |
main
| 6.5 |
6;6;6;8
|
3;4;3;3
|
https://iclr.cc/virtual/2022/poster/6244
|
Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning
|
https://github.com/PKU-MARL/TRPO-PPO-in-MARL
| null | 3.25 | 3.5 |
Poster
|
3;3;4;4
|
3;3;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
L2O;Generalization;Flatness;Entropy-SGD
| null | 1.75 | null | null |
iclr
| 0.333333 | 0 | null |
main
| 5.25 |
5;5;5;6
|
3;3;3;3
| null |
Generalizable Learning to Optimize into Wide Valleys
| null | null | 3 | 3.75 |
Reject
|
4;3;4;4
|
3;0;2;2
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;3;3
| null | null | null |
Node classification;graph filters;homophily degree;interaction probability;frequency distribution;filter bank;spectral graph neural networks
| null | 1 | null | null |
iclr
| 0.755929 | 0.755929 | null |
main
| 4.666667 |
3;5;6
|
2;2;3
| null |
Graph Information Matters: Understanding Graph Filters from Interaction Probability
| null | null | 2.333333 | 4.333333 |
Reject
|
4;4;5
|
2;0;1
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Federated Learning;Collaborative Learning
| null | 2.5 | null | null |
iclr
| -0.727607 | 0.889297 | null |
main
| 5.25 |
3;5;5;8
|
3;3;3;4
| null |
Adversarial Collaborative Learning on Non-IID Features
| null | null | 3.25 | 4.25 |
Reject
|
5;4;4;4
|
2;2;3;3
|
null |
University of Wisconsin-Madison; Chongqing University; Zhejiang University; RIKEN
|
2022
| 3.333333 |
https://iclr.cc/virtual/2022/poster/6038; None
| null | 0 | null | null | null |
3;4;3
| null |
Haobo Wang, Ruixuan Xiao, Yixuan Li, Lei Feng, Gang Niu, Gang Chen, Junbo Zhao
|
https://iclr.cc/virtual/2022/poster/6038
|
Partial Label Learning;Contrastive Learning;Prototype-based Disambiguation
| null | 3.666667 | null |
https://openreview.net/forum?id=EhYjZy6e1gJ
|
iclr
| 0 | 0 | null |
main
| 8 |
8;8;8
|
3;4;3
|
https://iclr.cc/virtual/2022/poster/6038
|
PiCO: Contrastive Label Disambiguation for Partial Label Learning
|
https://github.com/hbzju/PiCO
| null | 3.333333 | 3.333333 |
Oral
|
4;3;3
|
3;4;4
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
4;2;2;3;4
| null | null | null |
Adam;deep learning optimizer;momentum;nonconvex optimization;optimal batch size;SGD
| null | 2 | null | null |
iclr
| -0.825137 | 0.911089 | null |
main
| 4.2 |
1;3;5;6;6
|
1;1;3;4;3
| null |
The Number of Steps Needed for Nonconvex Optimization of a Deep Learning Optimizer is a Rational Function of Batch Size
| null | null | 2.4 | 3.4 |
Withdraw
|
5;3;3;3;3
|
4;0;2;2;2
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
4;2;3
| null | null | null |
Concept learning;Disentanglement learning;Explainability;Interpretability
| null | 3.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5
|
3;4;4
| null |
On The Quality Assurance Of Concept-Based Representations
| null | null | 3.666667 | 4 |
Reject
|
4;4;4
|
4;3;3
|
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
1;2;2;2
| null | null | null |
transfer learning;fine-tuning;layernorm;CLIP;prompt-tuning;adaptation;zero-shot;pretraining
| null | 2 | null | null |
iclr
| -0.333333 | 1 |
https://sites.google.com/view/adapt-large-scale-models
|
main
| 4.5 |
3;5;5;5
|
2;3;3;3
| null |
How to Adapt Your Large-Scale Vision-and-Language Model
| null | null | 2.75 | 3.75 |
Reject
|
4;4;4;3
|
1;2;3;2
|
null |
John A. Paulson School of Engineering and Applied Sciences, Harvard University; Department of Computer Science, Princeton University
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6725; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Jens Tuyls, Shunyu Yao, Sham M Kakade, Karthik Narasimhan
|
https://iclr.cc/virtual/2022/poster/6725
|
reinforcement learning;language understanding;text-based games
| null | 2.5 | null |
https://openreview.net/forum?id=Ek7PSN7Y77z
|
iclr
| -0.904534 | 0.57735 | null |
main
| 7 |
6;6;8;8
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/6725
|
Multi-Stage Episodic Control for Strategic Exploration in Text Games
|
https://github.com/princeton-nlp/XTX
| null | 3.75 | 3.75 |
Spotlight
|
5;4;3;3
|
3;3;0;4
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
uncertainty estimation;variational information bottleneck
| null | 2.5 | null | null |
iclr
| 0.662266 | 0.899229 | null |
main
| 4.75 |
3;5;5;6
|
2;3;4;4
| null |
Noise-Contrastive Variational Information Bottleneck Networks
| null | null | 3.25 | 3.25 |
Reject
|
3;3;3;4
|
2;3;2;3
|
null |
University of Guelph, Vector Institute, Samsung, SAIT AI Lab, Montreal; University of Guelph, Vector Institute; Vector Institute; POSTECH
|
2022
| 2 |
https://iclr.cc/virtual/2022/poster/6661; None
| null | 0 | null | null | null |
1;2;2;3
| null |
Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham W Taylor
|
https://iclr.cc/virtual/2022/poster/6661
| null | null | 2.25 | null |
https://openreview.net/forum?id=EnwCZixjSh
|
iclr
| -0.57735 | 1 | null |
main
| 6.5 |
6;6;6;8
|
3;3;3;4
|
https://iclr.cc/virtual/2022/poster/6661
|
On Evaluation Metrics for Graph Generative Models
|
https://github.com/uoguelph-mlrg/GGM-metrics
| null | 3.25 | 3.5 |
Poster
|
3;4;4;3
|
2;2;2;3
|
null | null |
2022
| 1.5 | null | null | 0 | null | null | null |
1;1;1;3
| null | null | null |
societal considerations of machine learning;fairness;safety;privacy;responsible AI;discrimination prevention;facial aesthetics;unconscious Bias
| null | 1.25 | null | null |
iclr
| -0.57735 | 0.522233 | null |
main
| 2.25 |
1;1;1;6
|
3;2;1;3
| null |
AestheticNet: Reducing bias in facial data sets under ethical considerations
| null | null | 2.25 | 4.5 |
Reject
|
4;5;5;4
|
1;0;1;3
|
null | null |
2022
| 1.8 | null | null | 0 | null | null | null |
1;1;3;2;2
| null | null | null |
few-shot learning;transfer learning
| null | 2.4 | null | null |
iclr
| -0.272166 | 0 | null |
main
| 4.4 |
3;3;5;5;6
|
3;3;3;3;3
| null |
A Study on Representation Transfer for Few-Shot Learning
| null | null | 3 | 4.4 |
Reject
|
5;4;5;4;4
|
2;2;3;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
neural architecture search;computer vision;convolutional neural networks
| null | 2.25 | null | null |
iclr
| -0.662266 | 0.662266 | null |
main
| 4.75 |
3;5;5;6
|
3;3;3;4
| null |
Fast and Efficient Once-For-All Networks for Diverse Hardware Deployment
| null | null | 3.25 | 3.5 |
Reject
|
4;4;4;2
|
2;2;3;2
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;3;3
| null | null | null |
Neural architecture search;transformer
| null | 3 | null | null |
iclr
| -0.802955 | 0 | null |
main
| 5.333333 |
3;5;8
|
3;3;3
| null |
UniNet: Unified Architecture Search with Convolution, Transformer, and MLP
| null | null | 3 | 4.333333 |
Withdraw
|
5;4;4
|
3;3;3
|
null |
Department of Computer Science and Engineering, Shanghai Jiao Tong University
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6491; None
| null | 0 | null | null | null |
2;4;3;2
| null |
Shuming Kong, Yanyan Shen, Linpeng Huang
|
https://iclr.cc/virtual/2022/poster/6491
|
Training bias;influence functions;data relabeling
| null | 3 | null |
https://openreview.net/forum?id=EskfH0bwNVn
|
iclr
| -0.707107 | 0 | null |
main
| 7 |
6;6;8;8
|
4;4;4;4
|
https://iclr.cc/virtual/2022/poster/6491
|
Resolving Training Biases via Influence-based Data Relabeling
| null | null | 4 | 4 |
Oral
|
4;5;4;3
|
3;4;3;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;2;2;4
| null | null | null | null | null | 2.5 | null | null |
iclr
| -0.288675 | 0.866025 | null |
main
| 6 |
5;5;6;8
|
3;2;3;4
| null |
Sample and Communication-Efficient Decentralized Actor-Critic Algorithms with Finite-Time Analysis
| null | null | 3 | 4 |
Reject
|
4;5;3;4
|
2;3;2;3
|
null |
Huawei Noah’s Ark Lab; National University of Singapore; AARC, Huawei Technologies; ShanghaiTech University
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/5967; None
| null | 0 | null | null | null |
2;1;2;4
| null |
Dapeng Hu, Shipeng Yan, Qizhengqiu Lu, Lanqing HONG, Hailin Hu, Yifan Zhang, Zhenguo Li, Xinchao Wang, Jiashi Feng
|
https://iclr.cc/virtual/2022/poster/5967
|
Pre-Training;Representation Learning;Continual Learning;Self-Supervised Learning
| null | 3.25 | null |
https://openreview.net/forum?id=EwqEx5ipbOu
|
iclr
| 0 | 0.229416 | null |
main
| 6.25 |
5;6;6;8
|
4;3;3;4
|
https://iclr.cc/virtual/2022/poster/5967
|
How Well Does Self-Supervised Pre-Training Perform with Streaming Data?
| null | null | 3.5 | 4 |
Poster
|
4;4;4;4
|
3;3;3;4
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
2;2;4;4
| null | null | null |
speech enhancement;audio-visual learning;speech dereverberation;room acoustics
| null | 2.75 | null | null |
iclr
| 0.140028 | -0.080845 | null |
main
| 5.75 |
3;6;6;8
|
4;3;4;4
| null |
Learning Audio-Visual Dereverberation
| null | null | 3.75 | 4.5 |
Reject
|
4;5;5;4
|
2;2;3;4
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;2;4;3
| null | null | null |
Deep neural networks;weight quantization;model compression;power-accuracy tradeoff;power consumption
| null | 1.75 | null | null |
iclr
| -0.522233 | 0.870388 | null |
main
| 4.25 |
3;3;5;6
|
1;2;3;3
| null |
Beyond Quantization: Power aware neural networks
| null | null | 2.25 | 3.25 |
Reject
|
4;3;4;2
|
1;0;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
trustworthy AI;fairness;generative model;total variation distance
| null | 2.25 | null | null |
iclr
| -0.406181 | 0 | null |
main
| 4.25 |
3;3;5;6
|
4;2;3;3
| null |
A Fair Generative Model Using Total Variation Distance
| null | null | 3 | 3.75 |
Reject
|
3;5;4;3
|
2;2;2;3
|
null | null |
2022
| 3.5 | null | null | 0 | null | null | null |
4;4;3;3
| null | null | null | null | null | 2.5 | null | null |
iclr
| 0.522233 | -0.57735 | null |
main
| 5.25 |
5;5;5;6
|
4;3;4;3
| null |
Learning from One and Only One Shot
| null | null | 3.5 | 4.25 |
Reject
|
5;4;3;5
|
4;2;1;3
|
null |
Robert Bosch Centre for Data Science and Artificial Intelligence, Department of Computer Science and Engineering, Indian Institute of Technology Madras, Chennai, India
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6917; None
| null | 0 | null | null | null |
2;2;3;3
| null |
Chandrasekar Subramanian, Balaraman Ravindran
|
https://iclr.cc/virtual/2022/poster/6917
|
causality;contextual bandits;causal inference;bandits
| null | 2.25 | null |
https://openreview.net/forum?id=F5Em8ASCosV
|
iclr
| 0 | 0.57735 | null |
main
| 5.5 |
5;5;6;6
|
3;3;3;4
|
https://iclr.cc/virtual/2022/poster/6917
|
Causal Contextual Bandits with Targeted Interventions
| null | null | 3.25 | 3 |
Poster
|
3;3;3;3
|
2;2;3;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
multi-agent;reinforcement learning;monotonicity constraint
| null | 2.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3
|
2;3;3
| null |
Revisiting the Monotonicity Constraint in Cooperative Multi-Agent Reinforcement Learning
| null | null | 2.666667 | 3.666667 |
Withdraw
|
5;3;3
|
3;2;2
|
null |
Technion; Language Technologies Institute, Carnegie Mellon University
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6366; None
| null | 0 | null | null | null |
2;2;3;4
| null |
Shaked Brody, Uri Alon, Eran Yahav
|
https://iclr.cc/virtual/2022/poster/6366
|
graph attention networks;dynamic attention;GAT;GNN
| null | 2.75 | null |
https://openreview.net/forum?id=F72ximsx7C1
|
iclr
| -0.288675 | 0.942809 | null |
main
| 6 |
5;5;6;8
|
3;3;3;4
|
https://iclr.cc/virtual/2022/poster/6366
|
How Attentive are Graph Attention Networks?
|
https://github.com/tech-srl/how_attentive_are_gats
| null | 3.25 | 4 |
Poster
|
5;4;3;4
|
3;2;3;3
|
null | null |
2022
| 1.5 | null | null | 0 | null | null | null |
1;2;1;2
| null | null | null | null | null | 2.5 | null | null |
iclr
| 0.889297 | 0.70014 | null |
main
| 3.25 |
1;3;3;6
|
2;2;3;3
| null |
Pretrained Language Models are Symbolic Mathematics Solvers too!
| null | null | 2.5 | 4.25 |
Reject
|
4;4;4;5
|
2;3;1;4
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
3;2;2;2
| null | null | null | null | null | 2.5 | null | null |
iclr
| 1 | 0.57735 | null |
main
| 4.5 |
3;5;5;5
|
2;2;3;3
| null |
Shapley-NAS: Discovering Operation Contribution for Neural Architecture Search
| null | null | 2.5 | 3.5 |
Withdraw
|
2;4;4;4
|
3;2;3;2
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;2;3
| null | null | null |
Neural Update Rules;Evolution
| null | 2.333333 | null | null |
iclr
| 0 | 0.5 | null |
main
| 3.666667 |
3;3;5
|
2;3;3
| null |
Evolving Neural Update Rules for Sequence Learning
| null | null | 2.666667 | 3 |
Reject
|
3;3;3
|
2;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
Stochastic gradient descent;bandwidth-based step size;non-asymptotic analysis
| null | 2.25 | null | null |
iclr
| -0.899229 | 0 | null |
main
| 4.75 |
3;5;5;6
|
3;3;3;3
| null |
Bandwidth-based Step-Sizes for Non-Convex Stochastic Optimization
| null | null | 3 | 3.75 |
Reject
|
5;4;3;3
|
2;2;2;3
|
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
2;1;2;2
| null | null | null | null | null | 1.75 | null | null |
iclr
| 0 | 0 | null |
main
| 4 |
3;3;5;5
|
3;4;3;4
| null |
AF$_2$: Adaptive Focus Framework for Aerial Imagery Segmentation
| null | null | 3.5 | 4 |
Reject
|
4;4;3;5
|
2;1;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
4;2;2;3
| null | null | null |
Explainability;Decision Boundary;Attribution;Adversarial Robustness
| null | 1 | null | null |
iclr
| 0.333333 | 0.870388 | null |
main
| 5.25 |
3;6;6;6
|
2;3;4;4
| null |
Robust Models Are More Interpretable Because Attributions Look Normal
| null | null | 3.25 | 3.25 |
Reject
|
3;3;4;3
|
0;2;2;0
|
null |
School of Computer Science, Carnegie Mellon University; Department of Mechanical Engineering, Carnegie Mellon University
|
2022
| 2.4 |
https://iclr.cc/virtual/2022/poster/6936; None
| null | 0 | null | null | null |
3;2;2;2;3
| null |
Zijie Li, Tianqin Li, Amir Barati Farimani
|
https://iclr.cc/virtual/2022/poster/6936
|
Point cloud super resolution;Temporal learning;Generative Adversarial Networks
| null | 3 | null |
https://openreview.net/forum?id=FEBFJ98FKx
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6;6
|
3;4;4;3;3
|
https://iclr.cc/virtual/2022/poster/6936
|
TPU-GAN: Learning temporal coherence from dynamic point cloud sequences
| null | null | 3.4 | 3.6 |
Poster
|
4;4;3;3;4
|
3;3;3;3;3
|
null |
CISPA Helmholtz Center for Information Security; Salesforce Research, University of Maryland, Max Planck Institute for Informatics
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/5964; None
| null | 0 | null | null | null |
3;3;3
| null |
Dingfan Chen, Ning Yu, Mario Fritz
|
https://iclr.cc/virtual/2022/poster/5964
|
membership inference attack;defense
| null | 2 | null |
https://openreview.net/forum?id=FEDfGWVZYIn
|
iclr
| 0 | 0 | null |
main
| 8 |
8;8;8
|
3;3;3
|
https://iclr.cc/virtual/2022/poster/5964
|
RelaxLoss: Defending Membership Inference Attacks without Losing Utility
|
https://github.com/DingfanChen/RelaxLoss
| null | 3 | 3.333333 |
Spotlight
|
4;4;2
|
3;0;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;2;3;2
| null | null | null |
Stochastic Deep Networks;LWTA;Meta-Learning
| null | 2.75 | null | null |
iclr
| 0.333333 | -0.174078 | null |
main
| 4.5 |
3;5;5;5
|
3;2;2;4
| null |
Stochastic Deep Networks with Linear Competing Units for Model-Agnostic Meta-Learning
| null | null | 2.75 | 3.25 |
Reject
|
3;3;3;4
|
3;3;3;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
1;2;4;3
| null | null | null | null | null | 3.25 | null | null |
iclr
| 0.760886 | 0.688247 | null |
main
| 4.75 |
3;5;5;6
|
3;4;3;4
| null |
Adaptive Pseudo-labeling for Quantum Calculations
| null | null | 3.5 | 3.75 |
Reject
|
3;3;4;5
|
2;3;4;4
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Generalization;correlation;experiments
| null | 2.25 | null | null |
iclr
| -0.333333 | 0.333333 | null |
main
| 3.5 |
3;3;3;5
|
2;3;3;3
| null |
Takeuchi's Information Criteria as Generalization Measures for DNNs Close to NTK Regime
| null | null | 2.75 | 3.25 |
Reject
|
3;3;4;3
|
2;2;2;3
|
null |
Intrinsic LLC; DeepMind, University of Edinburgh; DeepMind
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6489; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Todor Davchev, Oleg Sushkov, Jean-Baptiste Regli, Stefan Schaal, Yusuf Aytar, Markus Wulfmeier, Jon Scholz
|
https://iclr.cc/virtual/2022/poster/6489
|
goal-conditioned reinforcement learning;learning from demonstrations;long-horizon dexterous manipulation;bi-manual manipulation
| null | 2.25 | null |
https://openreview.net/forum?id=FKp8-pIRo3y
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
4;2;4;3
|
https://iclr.cc/virtual/2022/poster/6489
|
Wish you were here: Hindsight Goal Selection for long-horizon dexterous manipulation
| null | null | 3.25 | 3.5 |
Poster
|
3;3;4;4
|
3;2;2;2
|
null |
KAIST; DeepMind
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6824; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Jongmin Lee, Cosmin Paduraru, Daniel Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez
|
https://iclr.cc/virtual/2022/poster/6824
|
Offline Reinforcement Learning;Offline Constrained Reinforcement Learning;Stationary Distribution Correction Estimation
| null | 2.75 | null |
https://openreview.net/forum?id=FLA55mBee6Q
|
iclr
| 0 | 0 | null |
main
| 7 |
6;6;8;8
|
4;4;4;4
|
https://iclr.cc/virtual/2022/poster/6824
|
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation
| null | null | 4 | 3 |
Spotlight
|
3;3;4;2
|
3;2;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
model based reinforcement learning
| null | 2.666667 | null | null |
iclr
| 0 | -0.866025 | null |
main
| 4.333333 |
3;5;5
|
4;3;2
| null |
ED2: An Environment Dynamics Decomposition Framework for World Model Construction
|
https://github.com/ED2-source-code/ED2
| null | 3 | 4 |
Reject
|
4;5;3
|
2;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
experience replay;model-based reinforcement learning;sampling distribution;search-control;Dyna;stochastic gradient Langevin dynamics
| null | 2.25 | null | null |
iclr
| -0.333333 | 0.333333 | null |
main
| 3.5 |
3;3;3;5
|
3;3;2;3
| null |
Beyond Prioritized Replay: Sampling States in Model-Based Reinforcement Learning via Simulated Priorities
| null | null | 2.75 | 4.25 |
Reject
|
5;4;4;4
|
2;2;2;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;3;2
| null | null | null |
Image Generation;Adversarial Robustness;Perceptually Aligned Gradients
| null | 2 | null | null |
iclr
| -1 | 0 | null |
main
| 4.333333 |
3;5;5
|
3;3;3
| null |
BIGRoC: Boosting Image Generation via a Robust Classifier
| null | null | 3 | 3.666667 |
Reject
|
5;3;3
|
2;2;2
|
null |
; Stanford University, USA
|
2022
| 2.333333 |
https://iclr.cc/virtual/2022/poster/6148; None
| null | 0 | null | null | null |
2;2;3
| null |
Sabri Eyuboglu, Maya Varma, Khaled Saab, Jean-Benoit Delbrouck, Christopher Lee-Messer, Jared Dunnmon, James Y Zou, Christopher Re
|
https://iclr.cc/virtual/2022/poster/6148
|
robustness;subgroup analysis;error analysis;multimodal;slice discovery
| null | 2.666667 | null |
https://openreview.net/forum?id=FPCMqjI0jXN
|
iclr
| -1 | 0.866025 | null |
main
| 7.333333 |
6;8;8
|
2;3;4
|
https://iclr.cc/virtual/2022/poster/6148
|
Domino: Discovering Systematic Errors with Cross-Modal Embeddings
| null | null | 3 | 2.333333 |
Oral
|
3;2;2
|
2;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;2;3
| null | null | null |
machine learning;artificial intelligence;computer vision
| null | 2.5 | null | null |
iclr
| 0.333333 | 0.471405 | null |
main
| 4.75 |
3;3;3;10
|
1;3;4;4
| null |
Palette: Image-to-Image Diffusion Models
| null | null | 3 | 3.75 |
Withdraw
|
4;4;3;4
|
2;2;2;4
|
null |
University of Illinois at Chicago; Amazon; Shanghai Jiao Tong University
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/7180; None
| null | 0 | null | null | null |
2;3;3;2
| null |
Qitan Wu, Hengrui Zhang, Junchi Yan, David Wipf
|
https://iclr.cc/virtual/2022/poster/7180
|
Representation Learning on Graphs;Out-of-Distribution Generalization;Domain Shift;Graph Structure Learning;Invariant Models
| null | 2 | null |
https://openreview.net/forum?id=FQOC5u-1egI
|
iclr
| -0.522233 | 0.57735 | null |
main
| 5.75 |
5;6;6;6
|
3;4;4;3
|
https://iclr.cc/virtual/2022/poster/7180
|
Handling Distribution Shifts on Graphs: An Invariance Perspective
|
https://github.com/qitianwu/GraphOOD-EERM
| null | 3.5 | 3.25 |
Poster
|
4;2;4;3
|
2;3;3;0
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Computer Vision;Self-Supervised Learning;Representation Learning
| null | 2 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5;5
|
3;3;4;3
| null |
Constrained Mean Shift for Representation Learning
| null | null | 3.25 | 4 |
Withdraw
|
5;3;4;4
|
2;2;2;2
|
null |
Department of Chemical Engineering, Massachusetts Institute of Technology; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6883; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Wenhao Gao, Rocío Mercado, Connor Coley
|
https://iclr.cc/virtual/2022/poster/6883
|
molecular design;synthesis planning;tree generation;graph generation
| null | 3 | null |
https://openreview.net/forum?id=FRxhHdnxt1
|
iclr
| 0 | 0.870388 | null |
main
| 6.75 |
3;8;8;8
|
2;3;4;4
|
https://iclr.cc/virtual/2022/poster/6883
|
Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular Design
| null | null | 3.25 | 4 |
Spotlight
|
4;3;4;5
|
2;3;3;4
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;1;3
| null | null | null |
Self-Supervised Learning;Location Representation Learning;Double Fourier Sphere
| null | 2.25 | null | null |
iclr
| -0.132453 | 0.662266 | null |
main
| 4.75 |
3;5;5;6
|
3;3;3;4
| null |
Sphere2Vec: Self-Supervised Location Representation Learning on Spherical Surfaces
| null | null | 3.25 | 3.5 |
Reject
|
4;4;2;4
|
2;2;2;3
|
null | null |
2022
| 1.6 | null | null | 0 | null | null | null |
1;1;2;1;3
| null | null | null |
Federated Learning;Differential privacy;Feature importance;Deep neural networks
| null | 1.6 | null | null |
iclr
| 0 | 0.583333 | null |
main
| 2.2 |
1;1;3;3;3
|
2;1;2;2;4
| null |
Adaptive Differential Privacy in Federated Learning: A Priority-Based Approach
| null | null | 2.2 | 4 |
Withdraw
|
3;5;4;4;4
|
2;1;2;1;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;1;3
| null | null | null |
Neural-network-control;nonlinear systems;continuous control;adaptive control;task specification;signal temporal logic
| null | 2 | null | null |
iclr
| -0.5 | 0.5 | null |
main
| 4.333333 |
3;5;5
|
3;4;3
| null |
Non-Parametric Neuro-Adaptive Control Subject to Task Specifications
| null | null | 3.333333 | 3.666667 |
Reject
|
4;4;3
|
2;1;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
coding;communication;maximum entropy reinforcement learning;minimum entropy coupling
| null | 1.75 | null | null |
iclr
| -0.57735 | 0.57735 | null |
main
| 3.5 |
3;3;3;5
|
2;3;2;3
| null |
Communicating via Markov Decision Processes
| null | null | 2.5 | 3.5 |
Reject
|
4;3;4;3
|
2;1;2;2
|
null |
Probabilistic programming group, PLTC Section, University of Copenhagen, Copenhagen, Denmark; Department of Statistics, University of Oxford, Oxford, United Kingdom; Probabilistic programming group, SCARB / PLTC Section, Departments of Biology / Computer Science, University of Copenhagen, Copenhagen, Denmark; Biochemistry Department, Brandeis University, MA, USA
|
2022
| 3.333333 |
https://iclr.cc/virtual/2022/poster/6608; None
| null | 0 | null | null | null |
3;3;4
| null |
Lys Sanz Moreta, Ola Rønning, Ahmad Salim Al-Sibahi, Jotun Hein, Douglas Theobald, Thomas Hamelryck
|
https://iclr.cc/virtual/2022/poster/6608
|
biological sequences;variational autoencoders;latent representations;ornstein-uhlenbeck process;evolution
| null | 2 | null |
https://openreview.net/forum?id=FZoZ7a31GCW
|
iclr
| 0.5 | 0 | null |
main
| 7 |
5;8;8
|
3;3;3
|
https://iclr.cc/virtual/2022/poster/6608
|
Ancestral protein sequence reconstruction using a tree-structured Ornstein-Uhlenbeck variational autoencoder
| null | null | 3 | 4.333333 |
Poster
|
4;5;4
|
1;3;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Domain shift;uncertainty estimation;calibration;distributional robustness;unsupervised domain adaptation;semi-supervised learning
| null | 2 | null | null |
iclr
| 0.174078 | 0 | null |
main
| 5.25 |
5;5;5;6
|
3;3;3;3
| null |
Distributionally Robust Learning for Uncertainty Calibration under Domain Shift
| null | null | 3 | 3.75 |
Reject
|
3;3;5;4
|
2;2;2;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
Natural Language Processing;Decoding Algorithms
| null | 1.5 | null | null |
iclr
| -0.57735 | 0.57735 | null |
main
| 4 |
3;3;5;5
|
2;3;3;3
| null |
GSD: Generalized Stochastic Decoding
|
https://github.com/ginoailab/gsd.git
| null | 2.75 | 4.25 |
Withdraw
|
5;4;4;4
|
1;2;2;1
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
4;2;3
| null | null | null |
Object Detection;Detection Backbone;Neural Architecture Search;Zero-Shot NAS
| null | 3.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6
|
3;3;3
| null |
ZenDet: Revisiting Efficient Object Detection Backbones from Zero-Shot Neural Architecture Search
| null | null | 3 | 4 |
Reject
|
4;4;4
|
4;3;3
|
null | null |
2022
| 1.333333 | null | null | 0 | null | null | null |
1;1;2
| null | null | null |
Time Series-Text Representations;Pre-training;Mutilmodal
| null | 1.666667 | null | null |
iclr
| 0.5 | 0.5 | null |
main
| 2.333333 |
1;3;3
|
2;2;3
| null |
TS-BERT: A fusion model for Pre-trainning Time Series-Text Representations
| null | null | 2.333333 | 4.333333 |
Reject
|
4;5;4
|
2;1;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;2;4
| null | null | null |
Domain Adaptation;Optimization
| null | 2.75 | null | null |
iclr
| 0.522233 | 0.57735 | null |
main
| 5.75 |
5;5;5;8
|
4;3;3;4
| null |
A Closer Look at Smoothness in Domain Adversarial Training
| null | null | 3.5 | 3.25 |
Reject
|
2;3;4;4
|
2;2;3;4
|
null |
Technical University Berlin, Science of Intelligence
|
2022
| 2.333333 |
https://iclr.cc/virtual/2022/poster/7077; None
| null | 0 | null | null | null |
2;2;3
| null |
Marc Vischer, Robert Lange, Henning Sprekeler
|
https://iclr.cc/virtual/2022/poster/7077
|
Reinforcement Learning;Sparsity;Pruning;Lottery Ticket Hypothesis
| null | 3.333333 | null |
https://openreview.net/forum?id=Fl3Mg_MZR-
|
iclr
| -0.5 | 0.5 | null |
main
| 7 |
5;8;8
|
3;4;3
|
https://iclr.cc/virtual/2022/poster/7077
|
On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning
| null | null | 3.333333 | 3.666667 |
Spotlight
|
4;3;4
|
3;3;4
|
null |
Worcester Polytechnic Institute; Facebook AI Research; Brown University; UC Berkeley
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/5994; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo, Yuandong Tian
|
https://iclr.cc/virtual/2022/poster/5994
|
Optimization;Machine Learning
| null | 3.25 | null |
https://openreview.net/forum?id=FlwzVjfMryn
|
iclr
| 0 | 1 | null |
main
| 7 |
6;6;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/5994
|
Multi-objective Optimization by Learning Space Partition
| null | null | 3.5 | 4 |
Poster
|
4;4;4;4
|
3;3;3;4
|
null |
DeepMind, London, UK
|
2022
| 2 |
https://iclr.cc/virtual/2022/poster/7007; None
| null | 0 | null | null | null |
1;2;2;3
| null |
Ankesh Anand, Jacob C Walker, Yazhe Li, Eszter Vertes, Julian Schrittwieser, Sherjil Ozair, Theophane Weber, Jessica Hamrick
|
https://iclr.cc/virtual/2022/poster/7007
|
Self-Supervised Learning;Model-Based RL;Generalization in RL
| null | 3.25 | null |
https://openreview.net/forum?id=FmBegXJToY
|
iclr
| -0.301511 | 0.57735 | null |
main
| 7 |
6;6;8;8
|
4;2;4;4
|
https://iclr.cc/virtual/2022/poster/7007
|
Procedural generalization by planning with self-supervised world models
| null | null | 3.5 | 3.25 |
Poster
|
3;4;4;2
|
3;2;4;4
|
null |
Stanford University; University of Pennsylvania
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6042; None
| null | 0 | null | null | null |
2;2;3;3
| null |
Allan Zhou, Fahim Tajwar, Alexander Robey, Tom Knowles, George Pappas, Hamed Hassani, Chelsea Finn
|
https://iclr.cc/virtual/2022/poster/6042
|
invariance;augmentation;nuisance transformation;imbalance;long tail
| null | 3.25 | null |
https://openreview.net/forum?id=Fn7i_r5rR0q
|
iclr
| -0.157895 | -0.207514 | null |
main
| 6.25 |
5;6;6;8
|
4;2;2;3
|
https://iclr.cc/virtual/2022/poster/6042
|
Do deep networks transfer invariances across classes?
|
https://github.com/AllanYangZhou/generative-invariance-transfer
| null | 2.75 | 3.75 |
Poster
|
5;2;4;4
|
3;3;3;4
|
null |
Pennsylvania State University, University Park, PA 16802, USA
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/7152; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Mahmut Kandemir, Anand Sivasubramaniam
|
https://iclr.cc/virtual/2022/poster/7152
|
Graph Neural Networks;GNN;GCN;Distributed Training
| null | 2.25 | null |
https://openreview.net/forum?id=FndDxSz3LxQ
|
iclr
| -0.333333 | 0.333333 | null |
main
| 5.75 |
5;6;6;6
|
3;3;4;3
|
https://iclr.cc/virtual/2022/poster/7152
|
Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks
| null | null | 3.25 | 2.75 |
Poster
|
3;2;3;3
|
0;3;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;2;3
| null | null | null |
Optimization;Learning Rate Schedules;BERT
| null | 2.5 | null | null |
iclr
| -0.57735 | 0.57735 | null |
main
| 4.25 |
3;3;3;8
|
3;2;2;3
| null |
Learning Rate Grafting: Transferability of Optimizer Tuning
| null | null | 2.5 | 4 |
Reject
|
5;3;5;3
|
2;2;2;4
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;3;2
| null | null | null |
recurrent;parameters;degrees of freedom
| null | 2.5 | null | null |
iclr
| -0.904534 | 0 | null |
main
| 5.5 |
5;5;6;6
|
3;3;3;3
| null |
Recurrent Parameter Generators
| null | null | 3 | 4.25 |
Reject
|
5;5;4;3
|
2;2;3;3
|
null | null |
2022
| 1.8 | null | null | 0 | null | null | null |
2;1;1;3;2
| null | null | null |
graphs;networks;game theory;graph neural networks
| null | 1.8 | null | null |
iclr
| -0.516047 | 0.589768 | null |
main
| 4.6 |
3;3;5;6;6
|
4;2;4;4;4
| null |
Learning to Infer the Structure of Network Games
| null | null | 3.6 | 2.8 |
Reject
|
3;3;3;3;2
|
3;1;2;0;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
time series;time series segmentation;lstm;rnn;architecture;cnn;pyramid pooling;multi-scale pooling;sequence;encoder;decoder;resnet;step-wise
| null | 2 | null | null |
iclr
| -0.870388 | 0.522233 | null |
main
| 4.5 |
3;5;5;5
|
2;3;2;4
| null |
SegTime: Precise Time Series Segmentation without Sliding Window
| null | null | 2.75 | 3.75 |
Reject
|
5;4;3;3
|
2;2;2;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
AI Safety;verifiable learning;robustness;adversarial learning;proof systems
| null | 2.25 | null | null |
iclr
| -0.333333 | -0.333333 | null |
main
| 5.75 |
5;6;6;6
|
4;4;4;3
| null |
Learning to Give Checkable Answers with Prover-Verifier Games
| null | null | 3.75 | 2.5 |
Reject
|
3;3;1;3
|
2;2;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
Learning for Planning;Compositional Generalization
| null | 2.5 | null | null |
iclr
| -1 | 0.707107 | null |
main
| 4.5 |
3;3;6;6
|
3;2;3;4
| null |
Learning Rational Skills for Planning from Demonstrations and Instructions
| null | null | 3 | 3 |
Withdraw
|
4;4;2;2
|
2;3;3;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
conditional generation;diffusion models;decoupling;interpretability
| null | 2.25 | null | null |
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
3;3;4;3
| null |
ST-DDPM: Explore Class Clustering for Conditional Diffusion Probabilistic Models
| null | null | 3.25 | 3.25 |
Reject
|
4;3;3;3
|
2;2;2;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;2;3
| null | null | null |
scaling laws;neural networks;generalization;overparameterized models;underparameterized models
| null | 3.333333 | null | null |
iclr
| -0.866025 | 0.5 | null |
main
| 3.666667 |
3;3;5
|
2;3;3
| null |
Explaining Scaling Laws of Neural Network Generalization
| null | null | 2.666667 | 3 |
Reject
|
4;3;2
|
3;3;4
|
null | null |
2022
| 1.666667 | null | null | 0 | null | null | null |
1;1;3
| null | null | null |
Data Augmentation;Distribution Shift;Multi-Task Learning
| null | 1.333333 | null | null |
iclr
| 0 | -0.5 | null |
main
| 1.666667 |
1;1;3
|
2;3;2
| null |
Multi-Task Distribution Learning
| null | null | 2.333333 | 4 |
Reject
|
4;4;4
|
0;1;3
|
null |
Singapore University of Technology and Design; Royal Holloway, University of London; London School of Economics
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6694; None
| null | 0 | null | null | null |
2;3;4;2
| null |
Yun Kuen Cheung, Georgios Piliouras, Yixin Tao
|
https://iclr.cc/virtual/2022/poster/6694
|
learning in games;differential entropy
| null | 0 | null |
https://openreview.net/forum?id=Fza94Y8VS4a
|
iclr
| 0.688247 | 0.662266 | null |
main
| 6.25 |
5;6;6;8
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/6694
|
The Evolution of Uncertainty of Learning in Games
| null | null | 3.75 | 2.5 |
Poster
|
2;3;2;3
| null |
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
1;2;2;2
| null | null | null |
Speech Restoration;Neural Vocoder;Speech Denoising;Speech Declipping;Speech Dereverberation;Speech Super-resolution
| null | 2.25 | null | null |
iclr
| -0.96225 | 0.19245 |
https://anonymous20211004.github.io/demo-vf/
|
main
| 4.25 |
3;3;5;6
|
2;3;2;3
| null |
VoiceFixer: Toward General Speech Restoration with Neural Vocoder
| null | null | 2.5 | 4.5 |
Reject
|
5;5;4;4
|
2;2;2;3
|
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