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values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Curriculum Learning;Reinforcement learning;Hyper-network
| null | 1.5 | null | null |
iclr
| -0.752618 | 0 | null |
main
| 5.5 |
3;5;6;8
|
3;3;3;3
| null |
Learning Multi-Objective Curricula for Deep Reinforcement Learning
| null | null | 3 | 3.25 |
Withdraw
|
4;3;4;2
|
2;2;2;0
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;3;2;3
| null | null | null |
Label shift;optimal transport;Wasserstein distance;domain adaptation
| null | 2.5 | null | null |
iclr
| -0.688247 | 0 | null |
main
| 4.75 |
3;5;5;6
|
3;3;3;3
| null |
On Label Shift in Domain Adaptation via Wasserstein Distance
| null | null | 3 | 3.5 |
Withdraw
|
4;3;4;3
|
2;3;2;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
2;3;4
| null | null | null |
transferability metrics;fine-tuning;transfer learning;discrepancy measures;domain adaptation
| null | 2.666667 | null | null |
iclr
| 1 | 0 | null |
main
| 6 |
5;5;8
|
3;3;3
| null |
Newer is not always better: Rethinking transferability metrics, their peculiarities, stability and performance
| null | null | 3 | 3.333333 |
Reject
|
3;3;4
|
2;3;3
|
null |
Georgia Institute of Technology; Microsoft Azure AI; Amazon; Microsoft Research
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6667; None
| null | 0 | null | null | null |
3;4;2;3
| null |
Chen Liang, Haoming Jiang, Simiao Zuo, Xz W, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao
|
https://iclr.cc/virtual/2022/poster/6667
|
Training Large Transformer Models;Reducing Model Redundancy;Parameter Sensitivity;Adaptive Learning Rate Method;Model Generalization;Model Pruning
| null | 3 | null |
https://openreview.net/forum?id=cuvga_CiVND
|
iclr
| 0.333333 | -0.57735 | null |
main
| 6.5 |
6;6;6;8
|
4;3;4;3
|
https://iclr.cc/virtual/2022/poster/6667
|
No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models
|
https://github.com/cliang1453/SAGE
| null | 3.5 | 3.75 |
Poster
|
3;4;4;4
|
2;4;3;3
|
null |
Ant Group, China
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/5959; None
| null | 0 | null | null | null |
2;2;2;4
| null |
PengCheng Yang, Xiaoming Zhang, Wenpeng Zhang, Ming Yang, Hong Wei
|
https://iclr.cc/virtual/2022/poster/5959
|
Model parallelism;Pipeline parallelism;Distributed training
| null | 2.25 | null |
https://openreview.net/forum?id=cw-EmNq5zfD
|
iclr
| 0.916949 | 0.366508 | null |
main
| 6.25 |
3;6;8;8
|
3;4;4;3
|
https://iclr.cc/virtual/2022/poster/5959
|
Group-based Interleaved Pipeline Parallelism for Large-scale DNN Training
| null | null | 3.5 | 3.75 |
Poster
|
3;4;4;4
|
2;2;3;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;2;3
| null | null | null |
ML for PL/SE;ML models of code;Code representations;Brain representations;Cognitive neuroscience;Multivoxel pattern analysis;Representation decoding analysis;Representation similarity analysis;fMRI analysis
| null | 2.25 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5;5
|
3;4;3;3
| null |
Representations of Computer Programs in the Human Brain
|
https://github.com/anonmyous-author/anonymous-code
| null | 3.25 | 4 |
Reject
|
5;4;3;4
|
2;3;2;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null | null | null | 2 | null | null |
iclr
| -0.207514 | 0.927173 | null |
main
| 4.75 |
3;5;5;6
|
2;3;3;3
| null |
A Rate-Distortion Approach to Domain Generalization
| null | null | 2.75 | 4.25 |
Reject
|
5;3;4;5
|
3;2;1;2
|
null |
Department of Mathematics and the Norbert Wiener Center for Harmonic Analysis and Applications, University of Maryland, College Park, MD 20742, USA; Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, USA
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/7107; None
| null | 0 | null | null | null |
1;3;3;3
| null |
Gaurav Gupta, Xiongye Xiao, Radu Balan, Paul Bogdan
|
https://iclr.cc/virtual/2022/poster/7107
|
exponential operators;initial value problem;pade approximation;multiwavelets;partial differential equations
| null | 2.5 | null |
https://openreview.net/forum?id=d2TT6gK9qZn
|
iclr
| 0 | 0.83205 | null |
main
| 5.5 |
3;5;6;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/7107
|
Non-Linear Operator Approximations for Initial Value Problems
| null | null | 3.5 | 4 |
Poster
|
4;4;4;4
|
2;2;3;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;2;4
| null | null | null |
skill ranking;skill rating;skill
| null | 2.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 4 |
3;3;6
|
3;3;3
| null |
Match Prediction Using Learned History Embeddings
| null | null | 3 | 4 |
Reject
|
4;4;4
|
3;2;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
reinforcement learning;economics;simulation;multi-agent RL;equilibrium
| null | 2.75 | null | null |
iclr
| -0.927173 | 0.648886 | null |
main
| 4.75 |
3;5;5;6
|
2;3;4;3
| null |
Finding General Equilibria in Many-Agent Economic Simulations using Deep Reinforcement Learning
| null | null | 3 | 3.25 |
Reject
|
4;3;3;3
|
3;2;3;3
|
null |
Beijing Institute of Technology; The University of Hong Kong; University of Technology Sydney; University of Sydney; ByteDance AI Lab
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/6223; None
| null | 0 | null | null | null |
2;2;3;2
| null |
Shuo Yang, Peize Sun, Yi Jiang, Xiaobo Xia, Ruiheng Zhang, Zehuan Yuan, Changhu Wang, Ping Luo, Min Xu
|
https://iclr.cc/virtual/2022/poster/6223
| null | null | 2.75 | null |
https://openreview.net/forum?id=d5SCUJ5t1k
|
iclr
| 1 | 0.57735 | null |
main
| 6.5 |
5;5;8;8
|
3;3;3;4
|
https://iclr.cc/virtual/2022/poster/6223
|
Objects in Semantic Topology
| null | null | 3.25 | 3.5 |
Poster
|
3;3;4;4
|
2;3;3;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
2;3;3;4
| null | null | null |
Graph Neural Network;Graph Signal Processing;Graph Learning;Topology Inference;Algorithm Unrolling
| null | 2.75 | null | null |
iclr
| -0.555556 | 0 | null |
main
| 5.25 |
5;5;5;6
|
2;4;3;3
| null |
Learning Graph Structure from Convolutional Mixtures
| null | null | 3 | 3.25 |
Reject
|
2;5;4;2
|
2;2;3;4
|
null |
Department of Electrical Engineering, POSTECH; Department of Electrical Engineering, POSTECH; Graduate School of AI, POSTECH; Yonsei University
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/6263; None
| null | 0 | null | null | null |
3;2;2;2
| null |
Nam Hyeon-Woo, Moon Ye-Bin, Tae-Hyun Oh
|
https://iclr.cc/virtual/2022/poster/6263
|
Federated learning;Parameterization;Communication efficiency
| null | 2.75 | null |
https://openreview.net/forum?id=d71n4ftoCBy
|
iclr
| -0.57735 | -0.333333 | null |
main
| 6.5 |
6;6;6;8
|
4;3;3;3
|
https://iclr.cc/virtual/2022/poster/6263
|
FedPara: Low-rank Hadamard Product for Communication-Efficient Federated Learning
|
https://github.com/South-hw/FedPara_ICLR22
| null | 3.25 | 3 |
Poster
|
2;4;4;2
|
3;3;2;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;2;3
| null | null | null |
Self-Supervised Representation Learning;Residual Learning;Contrastive Learning
| null | 2 | null | null |
iclr
| -0.5 | 0 | null |
main
| 4 |
3;3;6
|
2;4;3
| null |
Residual Contrastive Learning: Unsupervised Representation Learning from Residuals
| null | null | 3 | 3.333333 |
Withdraw
|
4;3;3
|
1;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;3;2
| null | null | null |
Stochastic gradient descent;Finite-sum optimization;Variance reduction;Importance sampling
| null | 2.5 | null | null |
iclr
| 0.57735 | 0.57735 | null |
main
| 5.5 |
5;5;6;6
|
4;3;4;4
| null |
Stochastic Reweighted Gradient Descent
| null | null | 3.75 | 3.75 |
Reject
|
4;3;4;4
|
2;3;3;2
|
null |
National Taiwan University; Yonsei University; Waymo LLC; University of California, Merced; Google Research
|
2022
| 2.333333 |
https://iclr.cc/virtual/2022/poster/6346; None
| null | 0 | null | null | null |
2;3;2
| null |
Tsai-Shien Chen, Wei-Chih Hung, Hung-Yu Tseng, Shao-Yi Chien, Ming-Hsuan Yang
|
https://iclr.cc/virtual/2022/poster/6346
|
Self-supervised learning;Contrastive learning;Representation learning;Clustering-based learning
| null | 2.666667 | null |
https://openreview.net/forum?id=dDjSKKA5TP1
|
iclr
| 0 | -0.755929 | null |
main
| 6.333333 |
5;6;8
|
4;3;3
|
https://iclr.cc/virtual/2022/poster/6346
|
Incremental False Negative Detection for Contrastive Learning
|
https://github.com/tsaishien-chen/IFND
| null | 3.333333 | 4 |
Poster
|
4;4;4
|
3;2;3
|
null |
KAUST
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/5933; None
| null | 0 | null | null | null |
3;3;3
| null |
Biao Zhang, Peter Wonka
|
https://iclr.cc/virtual/2022/poster/5933
|
shape reconstruction single image;meta learning;few-shot learning;differentiable optimization;bi-level optimization
| null | 3 | null |
https://openreview.net/forum?id=dDo8druYppX
|
iclr
| 1 | 0 | null |
main
| 7.333333 |
6;8;8
|
3;3;3
|
https://iclr.cc/virtual/2022/poster/5933
|
Training Data Generating Networks: Shape Reconstruction via Bi-level Optimization
| null | null | 3 | 3.666667 |
Poster
|
3;4;4
|
3;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Structured Prediction;Energy network;Energy-based models;Loss-function learning;Dynamic loss function
| null | 2.75 | null | null |
iclr
| -0.333333 | 1 | null |
main
| 5.25 |
3;6;6;6
|
2;3;3;3
| null |
Structured Energy Network as a dynamic loss function. Case study. A case study with multi-label Classification
| null | null | 2.75 | 3.75 |
Reject
|
4;4;3;4
|
2;3;3;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;2;3;4
| null | null | null |
data poisoning
| null | 2.5 | null | null |
iclr
| -0.855186 | 0.863868 | null |
main
| 4.75 |
3;3;5;8
|
2;3;3;4
| null |
Defending Against Backdoor Attacks Using Ensembles of Weak Learners
| null | null | 3 | 3.5 |
Reject
|
4;4;3;3
|
2;1;3;4
|
null |
DeepMind London, UK
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/7009; None
| null | 0 | null | null | null |
4;3;3;3
| null |
Miruna Pîslar, David Szepesvari, Georg Ostrovski, Diana Borsa, Tom Schaul
|
https://iclr.cc/virtual/2022/poster/7009
|
exploration;mode-switching;reinforcement learning;Atari
| null | 3.25 | null |
https://openreview.net/forum?id=dEwfxt14bca
|
iclr
| 0.57735 | 0.904534 | null |
main
| 7 |
6;6;8;8
|
3;2;4;4
|
https://iclr.cc/virtual/2022/poster/7009
|
When should agents explore?
| null | null | 3.25 | 3.25 |
Spotlight
|
3;3;3;4
|
4;3;3;3
|
null |
Purdue University; UCSD CSE; University of Tuebingen; NVIDIA Research; MIT CSAIL; Imperial College London & Twitter
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/6212; None
| null | 0 | null | null | null |
2;3;4;4
| null |
Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, GOPINATH BALAMURUGAN, Michael Bronstein, Haggai Maron
|
https://iclr.cc/virtual/2022/poster/6212
|
Graph Neural Networks;Expressive power;Equivariance;Weisfeiler-Leman
| null | 2 | null |
https://openreview.net/forum?id=dFbKQaRk15w
|
iclr
| 0 | 1 | null |
main
| 7 |
6;6;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6212
|
Equivariant Subgraph Aggregation Networks
| null | null | 3.5 | 4 |
Spotlight
|
4;4;4;4
|
1;2;3;2
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;3;3
| null | null | null |
Feature Smoothing;Graph Neural Network;Graph Representation Learning
| null | 2.333333 | null | null |
iclr
| 0 | -0.5 | null |
main
| 5.666667 |
5;6;6
|
4;4;3
| null |
NAFS: A Simple yet Tough-to-Beat Baseline for Graph Representation Learning
| null | null | 3.666667 | 4 |
Reject
|
4;4;4
|
2;3;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Non-convex optimization;deep learning;quasi-Newton methods;adaptive cubic regularization
| null | 2 | null | null |
iclr
| 0 | 1 | null |
main
| 3.5 |
3;3;3;5
|
2;2;2;3
| null |
L-SR1 Adaptive Regularization by Cubics for Deep Learning
| null | null | 2.25 | 4 |
Reject
|
4;4;4;4
|
1;3;2;2
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;2;3
| null | null | null |
graph augmentation;mixup;graph classification;graphon
| null | 2.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 4.666667 |
3;3;8
|
3;3;3
| null |
G-Mixup: Graph Augmentation for Graph Classification
| null | null | 3 | 4 |
Reject
|
4;4;4
|
2;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;3;3;2
| null | null | null |
Federated Learning;Personalization;Generalization;Clustering;Convergence
| null | 2.25 | null | null |
iclr
| 0.899229 | 0 | null |
main
| 4.75 |
3;5;5;6
|
3;3;3;3
| null |
Personalized Federated Learning with Clustered Generalization
| null | null | 3 | 4.25 |
Withdraw
|
3;5;4;5
|
3;2;2;2
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null |
Hypernetworks;Partial Differential Equations;Fluid Dynamics
| null | 2.333333 | null | null |
iclr
| 0 | -0.5 | null |
main
| 6 |
5;5;8
|
3;4;3
| null |
Semi-supervised learning of partial differential operators and dynamical flows
| null | null | 3.333333 | 4 |
Reject
|
4;4;4
|
2;2;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null |
adversarial robustness;knowledge distillation;adversarial training;vision transformer
| null | 1.666667 | null | null |
iclr
| 0 | 0 | null |
main
| 4.666667 |
3;5;6
|
3;3;3
| null |
How and When Adversarial Robustness Transfers in Knowledge Distillation?
| null | null | 3 | 4 |
Withdraw
|
4;4;4
|
0;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
synthesis;music;generative;constraints
| null | 3 | null | null |
iclr
| 0 | 0.904534 | null |
main
| 5.5 |
5;5;6;6
|
2;3;4;4
| null |
Neurosymbolic Deep Generative Models for Sequence Data with Relational Constraints
| null | null | 3.25 | 3.5 |
Reject
|
3;4;4;3
|
2;3;3;4
|
null | null |
2022
| 3.25 | null | null | 0 | null | null | null |
4;3;3;3
| null | null | null |
unsupervised part decomposition;shape abstraction;3D shape representations;generative models;computer vision
| null | 3 | null | null |
iclr
| -0.57735 | 0.57735 | null |
main
| 6.5 |
5;5;8;8
|
3;3;3;4
| null |
Unsupervised Pose-Aware Part Decomposition for 3D Articulated Objects
| null | null | 3.25 | 3.5 |
Reject
|
4;4;2;4
|
3;3;3;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
Reinforcement Learning;Batch Reinforcement Learning;Policy Optimization;Overfitting
| null | 2 | null | null |
iclr
| -1 | 0 | null |
main
| 5.5 |
5;5;6;6
|
4;3;4;3
| null |
Avoiding Overfitting to the Importance Weights in Offline Policy Optimization
| null | null | 3.5 | 3.5 |
Reject
|
4;4;3;3
|
3;0;2;3
|
null |
TU Graz / CSH Vienna; Google Research, Blueshift Team; Google Research, Brain Team
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6604; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Rahim Entezari, Hanie Sedghi, Olga Saukh, Behnam Neyshabur
|
https://iclr.cc/virtual/2022/poster/6604
|
Permutation;Invariance;Mode Connectivity;Energy Barrier;Loss landscape;Deep Learning
| null | 3.25 | null |
https://openreview.net/forum?id=dNigytemkL
|
iclr
| -0.57735 | 1 | null |
main
| 7 |
6;6;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6604
|
The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks
|
https://github.com/rahimentezari/PermutationInvariance
| null | 3.5 | 3.75 |
Poster
|
4;4;4;3
|
3;3;3;4
|
null |
MIT
|
2022
| 3.75 |
https://iclr.cc/virtual/2022/poster/6848; None
| null | 0 | null | null | null |
4;4;4;3
| null |
Khashayar Gatmiry, Stefanie Jegelka, Jonathan Kelner
|
https://iclr.cc/virtual/2022/poster/6848
|
deep learning theory;adaptive kernel;robust deep learning;neural tangent kernel;adaptive generalization;non-convex optimization
| null | 0.25 | null |
https://openreview.net/forum?id=dPyRNUlttBv
|
iclr
| -0.333333 | -0.333333 | null |
main
| 7.5 |
6;8;8;8
|
4;3;4;4
|
https://iclr.cc/virtual/2022/poster/6848
|
Optimization and Adaptive Generalization of Three layer Neural Networks
| null | null | 3.75 | 2.5 |
Poster
|
3;3;1;3
|
0;1;0;0
|
null |
EPFL, Switzerland
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/5906; None
| null | 0 | null | null | null |
3;3;3;4
| null |
Zhenyu Zhu, Fabian Latorre, Grigorios Chrysos, Volkan Cevher
|
https://iclr.cc/virtual/2022/poster/5906
|
Polynomial Nets;Rademacher Complexity;Lipschitz constant;Coupled CP decomposition
| null | 2.5 | null |
https://openreview.net/forum?id=dQ7Cy_ndl1s
|
iclr
| 0 | 0.471405 | null |
main
| 6 |
5;5;6;8
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/5906
|
Controlling the Complexity and Lipschitz Constant improves Polynomial Nets
| null | null | 3.75 | 3 |
Poster
|
3;3;3;3
|
2;2;3;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;3;2;3
| null | null | null |
Anomaly Detection;GAN;Orthogonal Regularization;Bad-GAN
| null | 2.5 | null | null |
iclr
| -0.688247 | 0.688247 | null |
main
| 4.75 |
3;5;5;6
|
3;3;4;4
| null |
You May Need both Good-GAN and Bad-GAN for Anomaly Detection
| null | null | 3.5 | 3.5 |
Reject
|
4;4;3;3
|
2;2;2;4
|
null |
Technion; EPFL (LIONS)
|
2022
| 2.666667 |
https://iclr.cc/virtual/2022/poster/7173; None
| null | 0 | null | null | null |
3;2;3
| null |
Ali Kavis, Kfir Y Levy, Volkan Cevher
|
https://iclr.cc/virtual/2022/poster/7173
|
adaptive methods;nonconvex optimization;stochastic optimization;high probability bounds
| null | 2.666667 | null |
https://openreview.net/forum?id=dSw0QtRMJkO
|
iclr
| -1 | 0 | null |
main
| 6.666667 |
6;6;8
|
4;4;4
|
https://iclr.cc/virtual/2022/poster/7173
|
High Probability Bounds for a Class of Nonconvex Algorithms with AdaGrad Stepsize
| null | null | 4 | 3.666667 |
Poster
|
4;4;3
|
3;2;3
|
null |
JD Explore Academy, China; The University of Sydney, Australia
|
2022
| 3.5 |
https://iclr.cc/virtual/2022/poster/6020; None
| null | 0 | null | null | null |
3;4;3;4
| null |
Shaopeng Fu, Fengxiang He, Dacheng Tao
|
https://iclr.cc/virtual/2022/poster/6020
|
Bayesian inference;Markov chain Monte Carlo;machine unlearning
| null | 2.25 | null |
https://openreview.net/forum?id=dTqOcTUOQO
|
iclr
| -0.57735 | 0 | null |
main
| 6.75 |
3;8;8;8
|
4;4;4;4
|
https://iclr.cc/virtual/2022/poster/6020
|
Knowledge Removal in Sampling-based Bayesian Inference
|
https://github.com/fshp971/mcmc-unlearning
| null | 4 | 2.5 |
Poster
|
3;2;2;3
|
2;0;3;4
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
Visual transformers
| null | 1.333333 | null | null |
iclr
| -1 | 0.5 | null |
main
| 4 |
3;3;6
|
3;2;3
| null |
Local-Global Shifting Vision Transformers
| null | null | 2.666667 | 3.333333 |
Withdraw
|
4;4;2
|
1;1;2
|
null |
The University of Hong Kong; Hong Kong University of Science and Technology; Sun Yat-sen University; Huawei Noah’s Ark Lab
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6118; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Han Shi, JIAHUI GAO, Hang Xu, Xiaodan Liang, Zhenguo Li, Lingpeng Kong, Stephen Lee, James Kwok
|
https://iclr.cc/virtual/2022/poster/6118
|
BERT;Over-smoothing;Transformer
| null | 3.25 | null |
https://openreview.net/forum?id=dUV91uaXm3
|
iclr
| 0.57735 | 0.57735 | null |
main
| 7 |
6;6;8;8
|
4;3;4;4
|
https://iclr.cc/virtual/2022/poster/6118
|
Revisiting Over-smoothing in BERT from the Perspective of Graph
| null | null | 3.75 | 3.25 |
Spotlight
|
3;3;4;3
|
3;3;4;3
|
null |
Shirley Ryan AbilityLab, Department of Physical Medicine and Rehabilitation, Northwestern University; Shirley Ryan AbilityLab; Department of Neuroscience, Baylor College of Medicine
|
2022
| 1.5 | null | null | 0 | null | null | null |
2;1;1;2
| null | null | null |
human pose estimation;explainable AI;kinematics;gait;rehabilitation;activity recognition
| null | 2.5 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3;3
|
3;4;2;2
| null |
Spatiotemporal Characterization of Gait from Monocular Videos with Transformers
| null | null | 2.75 | 4.25 |
Withdraw
|
4;4;5;4
|
3;3;2;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Time Series Forecasting;U-Net;Transformers
| null | 2.5 | null | null |
iclr
| -0.57735 | 0.816497 | null |
main
| 3.5 |
3;3;3;5
|
2;3;3;4
| null |
Yformer: U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting
| null | null | 3 | 3.5 |
Reject
|
4;3;4;3
|
2;3;2;3
|
null |
Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences (ICT/CAS); SenseTime Research; University of Science and Technology of China; School of Computer Science, Faculty of Engineering, The University of Sydney; Huazhong University of Science and Technology
|
2022
| 4 |
https://iclr.cc/virtual/2022/poster/5918; None
| null | 0 | null | null | null |
4;4;4
| null |
Tao Huang, Zekang Li, Hua Lu, Yong Shan, Shusheng Yang, Yang Feng, Fei Wang, Shan You, Chang Xu
|
https://iclr.cc/virtual/2022/poster/5918
| null | null | 3.666667 | null |
https://openreview.net/forum?id=dZPgfwaTaXv
|
iclr
| 0 | 0 | null |
main
| 7.333333 |
6;8;8
|
4;4;4
|
https://iclr.cc/virtual/2022/poster/5918
|
Relational Surrogate Loss Learning
|
https://github.com/hunto/ReLoss
| null | 4 | 4 |
Poster
|
4;4;4
|
4;4;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
3;2;1;2
| null | null | null |
ImageNet;CNN design;dataset representativeness;empirical study
| null | 1.75 | null | null |
iclr
| 0.816497 | 0.57735 | null |
main
| 3.75 |
3;3;3;6
|
3;3;4;4
| null |
ImageNet as a Representative Basis for Deriving Generally Effective CNN Architectures
| null | null | 3.5 | 4 |
Withdraw
|
4;3;4;5
|
2;3;0;2
|
null |
Under double-blind review
|
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
spiking neural network;bio-plausible;deep learning;STDP
| null | 1.75 | null | null |
iclr
| -0.333333 | 1 | null |
main
| 4.5 |
3;5;5;5
|
2;3;3;3
| null |
Training Deep Spiking Neural Networks with Bio-plausible Learning Rules
| null | null | 2.75 | 3.75 |
Withdraw
|
4;3;4;4
|
2;2;2;1
|
null |
Université Paris-Saclay, Inria, CEA, Palaiseau, 91120, France
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/6724; None
| null | 0 | null | null | null |
3;3;4;3
| null |
Cédric Allain, Alexandre Gramfort, Thomas Moreau
|
https://iclr.cc/virtual/2022/poster/6724
|
Electrophysiology;Neuroscience;Temporal point processes;Convolutional Dictionary Learning
| null | 3.25 | null |
https://openreview.net/forum?id=d_2lcDh0Y9c
|
iclr
| 0.916949 | 0.863868 | null |
main
| 6.25 |
3;6;8;8
|
2;3;4;3
|
https://iclr.cc/virtual/2022/poster/6724
|
DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals
| null | null | 3 | 3.75 |
Poster
|
3;4;4;4
|
3;3;4;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
Prosody;Encoder-Decoder;Attention;Adaptive Duration Modification;Dynamic Time Warping
| null | 2 | null | null |
iclr
| 0.080845 | 0.37998 | null |
main
| 3.25 |
1;3;3;6
|
2;2;4;3
| null |
Adaptive Speech Duration Modification using a Deep-Generative Framework
| null | null | 2.75 | 3.5 |
Reject
|
4;4;2;4
|
1;2;2;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3
| null | null | null |
neural network selection;transfer learning;dynamical system;edge dynamics;network science
| null | 1.666667 | null | null |
iclr
| -0.5 | 0.5 | null |
main
| 5.333333 |
5;5;6
|
2;4;4
| null |
Neural Capacitance: A New Perspective of Neural Network Selection via Edge Dynamics
| null | null | 3.333333 | 2.333333 |
Reject
|
3;2;2
|
0;2;3
|
null |
New York University
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6026; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Nur Muhammad Shafiullah, Lerrel Pinto
|
https://iclr.cc/virtual/2022/poster/6026
|
Skill discovery;Incremental reinforcement learning
| null | 2.75 | null |
https://openreview.net/forum?id=dg79moSRqIo
|
iclr
| 0 | 0 |
https://notmahi.github.io/disk
|
main
| 6 |
6;6;6;6
|
4;4;3;3
|
https://iclr.cc/virtual/2022/poster/6026
|
One After Another: Learning Incremental Skills for a Changing World
|
https://github.com/notmahi/disk
| null | 3.5 | 4 |
Poster
|
5;3;4;4
|
3;3;3;2
|
null |
Graduate School of Information Science and Technology, the University of Tokyo; Graduate School of Information Science and Technology, the University of Tokyo; RIKEN Center for Advanced Intelligence Project
|
2022
| 3.75 |
https://iclr.cc/virtual/2022/poster/6811; None
| null | 0 | null | null | null |
3;4;4;4
| null |
Sho Okumoto, Taiji Suzuki
|
https://iclr.cc/virtual/2022/poster/6811
| null | null | 0 | null |
https://openreview.net/forum?id=dgxFTxuJ50e
|
iclr
| 0.333333 | 0 | null |
main
| 7.5 |
6;8;8;8
|
4;4;4;4
|
https://iclr.cc/virtual/2022/poster/6811
|
Learnability of convolutional neural networks for infinite dimensional input via mixed and anisotropic smoothness
| null | null | 4 | 3.5 |
Spotlight
|
3;5;3;3
| null |
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
3;2;2
| null | null | null |
Vision Transformers;Hardware-friendly;Soft Token Pruning
| null | 2 | null | null |
iclr
| -0.5 | 1 | null |
main
| 4.333333 |
3;5;5
|
2;3;3
| null |
HFSP: A Hardware-friendly Soft Pruning Framework for Vision Transformers
| null | null | 2.666667 | 3.666667 |
Withdraw
|
4;3;4
|
2;2;2
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null |
query refinement;reinforcement learning;self-supervised learning;question answering;search engines;large language models
| null | 1.666667 | null | null |
iclr
| -1 | 0.5 | null |
main
| 4 |
3;3;6
|
3;2;3
| null |
Boosting Search Engines with Interactive Agents
| null | null | 2.666667 | 3.666667 |
Reject
|
4;4;3
|
3;2;0
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
recommendation system;regularization;linear model
| null | 2.5 | null | null |
iclr
| 0.57735 | -0.333333 | null |
main
| 5.25 |
5;5;5;6
|
3;3;4;3
| null |
On the regularization landscape for the linear recommendation models
| null | null | 3.25 | 3.5 |
Reject
|
3;4;3;4
|
2;2;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
1;3;3;3
| null | null | null |
Logical Reasoning;Benchmark
| null | 2 | null | null |
iclr
| -0.392232 | 0.800641 | null |
main
| 5.5 |
3;5;6;8
|
3;3;3;4
| null |
NAIL: A Challenging Benchmark for Na\"ive Logical Reasoning
| null | null | 3.25 | 4 |
Reject
|
5;3;4;4
|
1;2;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Bayesian Deep learning;Expectation Propagation;Unsupervised Learning;Acoustic Modeling
| null | 2.5 | null | null |
iclr
| 0.866025 | 0.942809 | null |
main
| 5 |
3;5;6;6
|
2;3;3;3
| null |
EP-GAN: Unsupervised Federated Learning with Expectation-Propagation Prior GAN
| null | null | 2.75 | 3 |
Reject
|
2;3;4;3
|
2;2;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;2;2;3
| null | null | null |
Interpretability;Explainability
| null | 2.75 | null | null |
iclr
| -0.870388 | 0.522233 | null |
main
| 3.75 |
3;3;3;6
|
2;3;1;3
| null |
The Manifold Hypothesis for Gradient-Based Explanations
| null | null | 2.25 | 4.25 |
Reject
|
5;5;4;3
|
2;3;2;4
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null | null | null | 2.75 | null | null |
iclr
| 0 | 0.816497 | null |
main
| 5.25 |
5;5;5;6
|
3;3;2;4
| null |
The Low-Rank Simplicity Bias in Deep Networks
| null | null | 3 | 4 |
Reject
|
4;4;4;4
|
3;3;3;2
|
null |
Under double-blind review
|
2022
| 2 | null | null | 0 | null | null | null |
1;2;2;3
| null | null | null | null | null | 1.75 | null | null |
iclr
| -0.852803 | 1 | null |
main
| 3 |
1;3;3;5
|
1;2;2;3
| null |
On the Expressiveness, Predictability and Interpretability of Neural Temporal Point Processes
| null | null | 2 | 4.25 |
Withdraw
|
5;4;5;3
|
1;2;2;2
|
null |
Department of Mathematics, Brandeis University, Waltham, MA 02453, USA
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/7034; None
| null | 0 | null | null | null |
4;2;4;3
| null |
Wei Lu
|
https://iclr.cc/virtual/2022/poster/7034
| null | null | 2.25 | null |
https://openreview.net/forum?id=dpXL6lz4mOQ
|
iclr
| -0.471405 | 0.471405 | null |
main
| 6 |
5;5;6;8
|
3;2;3;3
|
https://iclr.cc/virtual/2022/poster/7034
|
LEARNING GUARANTEES FOR GRAPH CONVOLUTIONAL NETWORKS ON THE STOCHASTIC BLOCK MODEL
| null | null | 2.75 | 3.25 |
Poster
|
4;3;3;3
|
2;2;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;2;3;2
| null | null | null |
Novel Policy Discovery;Policy Diversity in Reinforcement Learning
| null | 2.5 | null | null |
iclr
| 0.57735 | 0.57735 | null |
main
| 4 |
3;3;5;5
|
2;3;3;3
| null |
Novel Policy Seeking with Constrained Optimization
| null | null | 2.75 | 3.25 |
Withdraw
|
3;3;3;4
|
3;2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Vision transformer;efficient transformer
| null | 2.25 | null | null |
iclr
| 1 | 0.333333 | null |
main
| 5.25 |
5;5;5;6
|
3;1;3;3
| null |
Self-Slimming Vision Transformer
| null | null | 2.5 | 4.25 |
Withdraw
|
4;4;4;5
|
2;2;2;3
|
null |
Autonomous Learning Robots, KIT, Germany; LCAS, University Of Lincoln, UK; Indian Institute Of Technology, Kanpur; Max Planck Institute for Intelligent Systems, T¨ubingen, Germany; Autonomous Learning Robots, KIT, Germany
|
2022
| 2 |
https://iclr.cc/virtual/2022/poster/6915; None
| null | 0 | null | null | null |
1;2;3;2
| null |
Vaisakh Shaj, Dieter Büchler, Rohit Sonker, Philipp Becker, Gerhard Neumann
|
https://iclr.cc/virtual/2022/poster/6915
|
State Space Models;Changing Dynamics;Recurrent Neural Networks;Multi Task Learning
| null | 2.5 | null |
https://openreview.net/forum?id=ds8yZOUsea
|
iclr
| 0 | 0.816497 | null |
main
| 6 |
5;5;6;8
|
2;2;3;3
|
https://iclr.cc/virtual/2022/poster/6915
|
Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios
| null | null | 2.5 | 3.75 |
Poster
|
4;4;3;4
|
2;2;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
1;3;3;2
| null | null | null |
Partial Differential Equations;operator learning;physics-informed;PINN;inverse problem;Navier-Stokes Equation
| null | 2.25 | null | null |
iclr
| 0.688247 | 0.648886 | null |
main
| 4.75 |
3;5;5;6
|
2;4;3;3
| null |
Physics-Informed Neural Operator for Learning Partial Differential Equations
| null | null | 3 | 2.5 |
Reject
|
2;2;3;3
|
1;3;3;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
Neural network quantization;Riemannian manifold;Information geometry;Mirror descent
| null | 2.75 | null | null |
iclr
| 0.57735 | 1 | null |
main
| 4.5 |
3;3;6;6
|
2;2;3;3
| null |
Riemannian Manifold Embeddings for Straight-Through Estimator
| null | null | 2.5 | 3.25 |
Reject
|
3;3;4;3
|
2;3;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
deep learning;classification;low precision;uniform symmetric quantization;binary neural network hardware
| null | 1.5 | null | null |
iclr
| 0.333333 | 1 | null |
main
| 4.5 |
3;5;5;5
|
2;3;3;3
| null |
CSQ: Centered Symmetric Quantization for Extremely Low Bit Neural Networks
| null | null | 2.75 | 4.25 |
Reject
|
4;5;4;4
|
2;0;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;3;2;3
| null | null | null |
graph sparsification;graph theory;machine learning;reinforcement learning
| null | 2 | null | null |
iclr
| 0 | 0.522233 | null |
main
| 3.75 |
3;3;3;6
|
3;2;4;4
| null |
SparRL: Graph Sparsification via Deep Reinforcement Learning
| null | null | 3.25 | 4 |
Reject
|
4;4;4;4
|
2;2;2;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Complex hyperbolic embeddings;hierarchical data embeddings;taxonomy embeddings
| null | 2.5 | null | null |
iclr
| 0.333333 | -0.57735 | null |
main
| 5.25 |
5;5;5;6
|
4;4;3;3
| null |
Unit Ball Model for Embedding Hierarchical Structures in the Complex Hyperbolic Space
| null | null | 3.5 | 3.75 |
Reject
|
4;4;3;4
|
2;2;3;3
|
null | null |
2022
| 2.6 |
https://iclr.cc/virtual/2022/poster/6287; None
| null | 0 | null | null | null |
2;2;3;3;3
| null |
Kwonjoon Lee, Huiwen Chang, Lu Jiang, Han Zhang, Zhuowen Tu, Ce Liu
|
https://iclr.cc/virtual/2022/poster/6287
| null | null | 3 | null |
https://openreview.net/forum?id=dwg5rXg1WS_
|
iclr
| 1 | 0.408248 | null |
main
| 6.4 |
6;6;6;6;8
|
4;4;3;3;4
|
https://iclr.cc/virtual/2022/poster/6287
|
ViTGAN: Training GANs with Vision Transformers
| null | null | 3.6 | 4.2 |
Spotlight
|
4;4;4;4;5
|
3;3;3;2;4
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;1;4;3
| null | null | null |
self-supervised learning;representation disentanglement
| null | 2.5 | null | null |
iclr
| -0.889297 | 0.990148 | null |
main
| 5.25 |
3;5;5;8
|
2;3;3;4
| null |
Disentangling Properties of Contrastive Methods
| null | null | 3 | 3.5 |
Reject
|
4;4;4;2
|
3;2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
1;2;3;3
| null | null | null |
spectral bias;generalization;function frequency;image classification
| null | 2.5 | null | null |
iclr
| 0.57735 | -0.57735 | null |
main
| 5.5 |
3;3;8;8
|
3;3;3;2
| null |
Spectral Bias in Practice: the Role of Function Frequency in Generalization
| null | null | 2.75 | 4.25 |
Reject
|
4;4;4;5
|
2;3;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;3
| null | null | null |
System identification;Model predictive control;Subspace state-space system identification
| null | 1.666667 | null | null |
iclr
| -1 | 1 | null |
main
| 4.666667 |
3;5;6
|
1;3;4
| null |
Subspace State-Space Identification and Model Predictive Control of Nonlinear Dynamical Systems Using Deep Neural Network with Bottleneck
| null | null | 2.666667 | 3.333333 |
Reject
|
5;3;2
|
1;2;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Latent space;Bayesian Optimization;Collision
| null | 2 | null | null |
iclr
| -0.707107 | 0.707107 | null |
main
| 4 |
3;3;5;5
|
2;3;4;3
| null |
Learning Representation for Bayesian Optimization with Collision-free Regularization
| null | null | 3 | 4 |
Reject
|
4;5;3;4
|
2;2;2;2
|
null |
Department of Computational Linguistics and Digital Humanities, Trier University; Department of Applied Econometrics, Karlsruhe Institute of Technology; Department of Analytics and Statistics, Karlsruhe Institute of Technology
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/6550; None
| null | 0 | null | null | null |
2;2;2;3
| null |
Nils Koster, Oliver Grothe, Achim Rettinger
|
https://iclr.cc/virtual/2022/poster/6550
|
Neural Networks;Supermask;Lottery Ticket Hypothesis;Pruning;Weight Initialization;Interpretation;Subnetworks
| null | 2.5 | null |
https://openreview.net/forum?id=e0jtGTfPihs
|
iclr
| 0.942809 | 0.471405 |
Not provided
|
main
| 6 |
5;5;6;8
|
3;2;3;3
|
https://iclr.cc/virtual/2022/poster/6550
|
Signing the Supermask: Keep, Hide, Invert
|
Not provided
| null | 2.75 | 4.25 |
Poster
|
4;4;4;5
|
3;2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;3;2;2
| null | null | null |
spiking neural networks;neuromorphic engineering;adversarial attacks;dynamic vision sensors
| null | 2.5 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5;5
|
3;3;4;3
| null |
Adversarial Attacks on Spiking Convolutional Networks for Event-based Vision
| null | null | 3.25 | 3.75 |
Reject
|
5;2;4;4
|
3;3;2;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
accelerator;codesign;hard constraint;NAS
| null | 1.75 | null | null |
iclr
| -0.870388 | 1 | null |
main
| 3.75 |
3;3;3;6
|
3;3;3;4
| null |
ConCoDE: Hard-constrained Differentiable Co-Exploration Method for Neural Architectures and Hardware Accelerators
| null | null | 3.25 | 3.25 |
Withdraw
|
4;3;4;2
|
1;2;2;2
|
null |
Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6284; None
| null | 0 | null | null | null |
2;4;3;3
| null |
Arda Sahiner, Tolga Ergen, Batu Ozturkler, Burak Bartan, John M Pauly, Morteza Mardani, Mert Pilanci
|
https://iclr.cc/virtual/2022/poster/6284
|
Wasserstein GAN;convex-concave game;saddle points;generative models;quadratic;polynomial activation;convex duality
| null | 3 | null |
https://openreview.net/forum?id=e2Lle5cij9D
|
iclr
| 0.174078 | -0.333333 | null |
main
| 7.25 |
5;8;8;8
|
4;3;4;4
|
https://iclr.cc/virtual/2022/poster/6284
|
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions
|
https://github.com/ardasahiner/ProCoGAN
| null | 3.75 | 4.25 |
Poster
|
4;5;3;5
|
2;4;3;3
|
null |
Google Research, Brain Team
|
2022
| 3.4 |
https://iclr.cc/virtual/2022/poster/6245; None
| null | 0 | null | null | null |
2;3;4;4;4
| null |
Ting Chen, Saurabh Saxena, Lala Li, David Fleet, Geoffrey Hinton
|
https://iclr.cc/virtual/2022/poster/6245
|
language modeling;object detection
| null | 2.6 | null |
https://openreview.net/forum?id=e42KbIw6Wb
|
iclr
| 0.912871 | 0.612372 | null |
main
| 7.2 |
6;6;8;8;8
|
3;4;4;4;4
|
https://iclr.cc/virtual/2022/poster/6245
|
Pix2seq: A Language Modeling Framework for Object Detection
|
https://github.com/google-research/pix2seq
| null | 3.8 | 4 |
Poster
|
3;3;5;5;4
|
3;2;2;2;4
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null | null | null | 2.75 | null | null |
iclr
| 0.324443 | 0.132453 |
Not provided
|
main
| 4.75 |
3;5;5;6
|
3;4;3;3
| null |
Ontology-Driven Semantic Alignment of Artificial Neurons and Visual Concepts
|
Not provided
| null | 3.25 | 4 |
Withdraw
|
4;4;3;5
|
2;3;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;3;2
| null | null | null |
Few-Shot Learning;Meta learning;Hypernetworks;Transformers
| null | 2.25 | null | null |
iclr
| -0.816497 | -0.333333 | null |
main
| 4.5 |
3;5;5;5
|
3;3;3;2
| null |
Revisiting Linear Decision Boundaries for Few-Shot Learning with Transformer Hypernetworks
| null | null | 2.75 | 4 |
Withdraw
|
5;3;4;4
|
2;3;2;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;1;3;3
| null | null | null |
Story Generation;Story Evaluation;Dataset;Storytelling;NLP;Evaluation;Contrastive learning;Language Models;Fine Tuning;Efficiency;Interactive Machine Learning;Narrative;Creativity;Human Centered AI;Creativity;Generative Models;World Models;Reader Models
| null | 2.75 | null | null |
iclr
| 1 | 0.57735 | null |
main
| 4 |
3;3;5;5
|
2;2;3;2
| null |
Cut the CARP: Fishing for zero-shot story evaluation
| null | null | 2.25 | 3.5 |
Withdraw
|
3;3;4;4
|
3;2;3;3
|
null | null |
2022
| 2.833333 | null | null | 0 | null | null | null |
2;3;3;3;3;3
| null | null | null |
Graph Partitioning;Community Detection;Inductive Graph Embedding
| null | 2.666667 | null | null |
iclr
| -0.478091 | 0.472456 | null |
main
| 4.666667 |
3;3;5;5;6;6
|
3;3;4;3;4;3
| null |
Trading Quality for Efficiency of Graph Partitioning: An Inductive Method across Graphs
| null | null | 3.333333 | 2.666667 |
Reject
|
3;3;3;3;3;1
|
2;2;3;3;3;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;2;3;4
| null | null | null |
online kernel methods;hebbian learning;similarity matching
| null | 2.75 | null | null |
iclr
| 0.923381 | -0.927173 | null |
main
| 6.25 |
5;6;6;8
|
4;4;4;3
| null |
Online approximate factorization of a kernel matrix by a Hebbian neural network
| null | null | 3.75 | 3.5 |
Reject
|
2;3;4;5
|
2;2;3;4
|
null |
School of Computer Science, Wuhan University; Institute for Artificial Intelligence, Peking University & BIGAI; Department of Computer Science, Purdue University
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6134; None
| null | 0 | null | null | null |
3;3;3;3;3
| null |
Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li
|
https://iclr.cc/virtual/2022/poster/6134
|
Graph Neural Network;Spectral Graph Theory;System Stability
| null | 2.2 | null |
https://openreview.net/forum?id=e95i1IHcWj
|
iclr
| -0.645497 | 0.745356 | null |
main
| 6.8 |
6;6;6;8;8
|
3;3;1;4;4
|
https://iclr.cc/virtual/2022/poster/6134
|
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks
|
https://github.com/Graph-COM/PEG
| null | 3 | 4 |
Poster
|
4;4;5;4;3
|
2;3;1;2;3
|
null | null |
2022
| 2.2 | null | null | 0 | null | null | null |
3;2;2;2;2
| null | null | null |
Efficient Inference;N:M Sparsification;Quantization;Transformer networks
| null | 2.6 | null | null |
iclr
| -0.875 | -0.25 | null |
main
| 4.6 |
3;5;5;5;5
|
3;3;2;3;3
| null |
HoloFormer: Deep Compression of Pre-Trained Transforms via Unified Optimization of N:M Sparsity and Integer Quantization
| null | null | 2.8 | 3.6 |
Withdraw
|
5;3;3;3;4
|
3;3;2;3;2
|
null |
Department of Computer Science and Technology, Institute for AI Industry Research, Institute for Artificial Intelligence, Tsinghua University, Beijing, 100084, China
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/5987; None
| null | 0 | null | null | null |
4;3;3;3
| null |
Zonghan Yang, Yang Liu
|
https://iclr.cc/virtual/2022/poster/5987
|
prefix-tuning;pretrained language models;text classification;robustness in NLP;optimal control
| null | 3.5 | null |
https://openreview.net/forum?id=eBCmOocUejf
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
4;2;3;3
|
https://iclr.cc/virtual/2022/poster/5987
|
On Robust Prefix-Tuning for Text Classification
|
https://github.com/minicheshire/Robust-Prefix-Tuning
| null | 3 | 3 |
Poster
|
2;4;3;3
|
4;3;3;4
|
null |
Machine Learning Department, Carnegie Mellon University
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/6871; None
| null | 0 | null | null | null |
2;3;4;4
| null |
Bingbin Liu, Elan Rosenfeld, Pradeep K Ravikumar, Andrej Risteski
|
https://iclr.cc/virtual/2022/poster/6871
|
noise contrastive estimation;contrastive learning;unsupervised learning;theory
| null | 2 | null |
https://openreview.net/forum?id=eBS-3YiaIL-
|
iclr
| -0.707107 | 0.57735 | null |
main
| 7 |
6;6;8;8
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/6871
|
Analyzing and Improving the Optimization Landscape of Noise-Contrastive Estimation
| null | null | 3.75 | 3 |
Spotlight
|
3;4;3;2
|
2;3;0;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;2;3
| null | null | null | null | null | 1.666667 | null | null |
iclr
| -0.5 | -0.5 | null |
main
| 5.333333 |
5;5;6
|
3;4;3
| null |
Adaptive Unbiased Teacher for Cross-Domain Object Detection
| null | null | 3.333333 | 4.333333 |
Withdraw
|
5;4;4
|
2;2;1
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;2;3
| null | null | null | null | null | 2 | null | null |
iclr
| -0.777778 | 0.555556 | null |
main
| 4.25 |
3;3;5;6
|
2;3;3;3
| null |
Pretraining for Language Conditioned Imitation with Transformers
| null | null | 2.75 | 3.75 |
Reject
|
4;4;4;3
|
1;2;2;3
|
null |
Paper under double-blind review
|
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Trustworthy Machine Learning;Model Extraction Attacks;Hardness of Samples
| null | 2.5 | null | null |
iclr
| 0 | 0.826811 | null |
main
| 3.75 |
1;3;5;6
|
1;3;3;3
| null |
HODA: Protecting DNNs Against Model Extraction Attacks via Hardness of Samples
| null | null | 2.5 | 4 |
Reject
|
4;4;4;4
|
2;3;3;2
|
null | null |
2022
| 1.333333 | null | null | 0 | null | null | null |
1;2;1
| null | null | null |
Reinforcement learning;Hamiltonian canonical equation;ODE;World model;Sample efficiency
| null | 1.666667 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3
|
2;2;2
| null |
Model-based Reinforcement Learning with a Hamiltonian Canonical ODE Network
| null | null | 2 | 4 |
Reject
|
4;3;5
|
2;2;1
|
null | null |
2022
| 0 | null | null | 0 | null | null | null | null | null |
Dan Hendrycks, Mantas Mazeika, Andy Zou, Sahil Patel, Christine Zhu, Jesus Navarro, Dawn Song, Bo Li, Jacob Steinhardt
| null |
Transformers;RL;data bias;reward bias;machine ethics;value learning;safe exploration
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 0 | null | null | null |
Assessing and Developing Text-Based Agents for Morally Salient Scenarios
| null | null | 0 | 0 |
Withdraw
| null | null |
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Adversarial Robustness;Adversarial Defense;Adversarial Training
| null | 2.25 | null | null |
iclr
| 0 | 0.272166 | null |
main
| 4.25 |
3;3;5;6
|
3;3;2;4
| null |
Towards Achieving Adversarial Robustness Beyond Perceptual Limits
| null | null | 3 | 4 |
Withdraw
|
4;4;4;4
|
2;2;2;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;2;4
| null | null | null |
model compression;low-rankness;sparsity;tensor
| null | 3 | null | null |
iclr
| -0.889297 | 0.889297 | null |
main
| 5.75 |
3;6;6;8
|
3;4;4;4
| null |
SPARK: co-exploring model SPArsity and low-RanKness for compact neural networks
| null | null | 3.75 | 3.5 |
Reject
|
5;3;3;3
|
2;3;3;4
|
null |
N/A
|
2022
| 2.25 | null | null | 0 | null | null | null |
3;2;2;2
| null | null | null |
network pruning;meta pruning;self-supervision;multi-task pruning
| null | 2.5 | null | null |
iclr
| 1 | 1 | null |
main
| 4.5 |
3;5;5;5
|
2;3;3;3
| null |
Vote for Nearest Neighbors Meta-Pruning of Self-Supervised Networks
| null | null | 2.75 | 3.75 |
Withdraw
|
3;4;4;4
|
3;2;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
self-supervised learning;contrastive learning;multi-domain data;unsupervised learning
| null | 2.666667 | null | null |
iclr
| 0 | 0.5 | null |
main
| 5.666667 |
5;6;6
|
3;3;4
| null |
Multi-Domain Self-Supervised Learning
| null | null | 3.333333 | 4 |
Reject
|
4;4;4
|
3;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Domain generalization Meta-learning Transfer learning Generalization Bound
| null | 2.5 | null | null |
iclr
| -0.923381 | 0.760886 | null |
main
| 4.75 |
3;5;5;6
|
2;2;3;4
| null |
Discrepancy-Optimal Meta-Learning for Domain Generalization
| null | null | 2.75 | 3.5 |
Reject
|
5;4;3;2
|
2;3;2;3
|
null |
Microsoft Research Asia; Microsoft Research New England
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/6304; None
| null | 0 | null | null | null |
4;3;3;3
| null |
Jiaxin Shi, Chang Liu, Lester Mackey
|
https://iclr.cc/virtual/2022/poster/6304
|
Stein's method;Sampling;Mirror descent;Natural gradient descent;Probabilistic inference;Bayesian inference;Post-selection inference;Stein operators
| null | 3.25 | null |
https://openreview.net/forum?id=eMudnJsb1T5
|
iclr
| -0.816497 | 0.707107 | null |
main
| 8 |
6;8;8;10
|
3;4;3;4
|
https://iclr.cc/virtual/2022/poster/6304
|
Sampling with Mirrored Stein Operators
| null | null | 3.5 | 3.25 |
Spotlight
|
4;3;3;3
|
4;3;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
generalisation;function space;PAC-Bayes;NNGP;orthants;margin
| null | 1.75 | null | null |
iclr
| -0.57735 | 0 | null |
main
| 5.5 |
5;5;6;6
|
3;3;3;3
| null |
On the Implicit Biases of Architecture & Gradient Descent
| null | null | 3 | 2.75 |
Reject
|
3;3;3;2
|
2;1;2;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Simulation;Graph Neural Network;Boundary Conditions;Granular Flow;Physics Application
| null | 1.75 | null | null |
iclr
| 0.333333 | 1 | null |
main
| 5.25 |
5;5;5;6
|
3;3;3;4
| null |
Boundary Graph Neural Networks for 3D Simulations
| null | null | 3.25 | 3.75 |
Reject
|
4;3;4;4
|
2;0;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
3;2;2;1
| null | null | null |
Incremental learning;Domain-aware;EM algorithm
| null | 2.25 | null | null |
iclr
| -0.333333 | -0.870388 | null |
main
| 5.25 |
5;5;5;6
|
3;3;2;1
| null |
General Incremental Learning with Domain-aware Categorical Representations
| null | null | 2.25 | 4.25 |
Withdraw
|
5;4;4;4
|
3;2;2;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null | null | null | 2.25 | null | null |
iclr
| -0.080845 | 0.594089 | null |
main
| 5.25 |
3;5;5;8
|
2;1;2;3
| null |
Task Conditioned Stochastic Subsampling
| null | null | 2 | 3.5 |
Reject
|
3;5;3;3
|
0;4;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;2;3;2
| null | null | null | null | null | 1.5 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5;5
|
3;2;4;4
| null |
Geometric Random Walk Graph Neural Networks via Implicit Layers
| null | null | 3.25 | 4.25 |
Reject
|
4;5;4;4
|
2;0;2;2
|
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