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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
null |
Mila - Quebec AI Institute, Universit ´e de Montr ´eal, Quebec, Canada
|
2022
| 3.333333 |
https://iclr.cc/virtual/2022/poster/7092; None
| null | 0 | null | null | null |
3;4;3
| null |
Kartik Ahuja, Jason Hartford, Yoshua Bengio
|
https://iclr.cc/virtual/2022/poster/7092
|
representation learning;equivariance;independent component analysis;ICA;autoencoders
| null | 0 | null |
https://openreview.net/forum?id=g5ynW-jMq4M
|
iclr
| 0.866025 | -1 | null |
main
| 6.666667 |
6;6;8
|
4;4;3
|
https://iclr.cc/virtual/2022/poster/7092
|
Properties from mechanisms: an equivariance perspective on identifiable representation learning
| null | null | 3.666667 | 3 |
Spotlight
|
3;2;4
| null |
null | null |
2022
| 2.8 | null | null | 0 | null | null | null |
3;2;2;3;4
| null | null | null |
positional encoding;fourier features;coordinate-based mlp
| null | 2.4 | null | null |
iclr
| 0 | 0.269665 | null |
main
| 5.4 |
3;3;5;6;10
|
3;4;2;3;4
| null |
Generalized Fourier Features for Coordinate-Based Learning of Functions on Manifolds
| null | null | 3.2 | 4 |
Reject
|
4;4;4;4;4
|
2;2;2;2;4
|
null |
University of Toronto, Vector Institute, Hospital of Sickkids; Microsoft Research
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6355; None
| null | 0 | null | null | null |
3;3;3
| null |
Chun-Hao Chang, Rich Caruana, Anna Goldenberg
|
https://iclr.cc/virtual/2022/poster/6355
|
Generalized Additive Model;Deep Learning Architecture;Interpretability
| null | 1.666667 | null |
https://openreview.net/forum?id=g8NJR6fCCl8
|
iclr
| 0.866025 | 1 | null |
main
| 7 |
5;8;8
|
2;4;4
|
https://iclr.cc/virtual/2022/poster/6355
|
NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning
| null | null | 3.333333 | 3 |
Spotlight
|
2;3;4
|
2;0;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
Long-Tailed Recognition;Latent Category
| null | 2.5 | null | null |
iclr
| -0.973329 | 0.648886 | null |
main
| 4.75 |
3;5;5;6
|
2;4;3;3
| null |
LONG-TAILED RECOGNITION BY LEARNING FROM LATENT CATEGORIES
| null | null | 3 | 4 |
Withdraw
|
5;4;4;3
|
2;3;2;3
|
null | null |
2022
| 1.25 | null | null | 0 | null | null | null |
1;1;1;2
| null | null | null |
Auditory attention;Gramian Angular Difference Field;Electroencephalography
| null | 1.25 | null | null |
iclr
| -0.57735 | 0.57735 | null |
main
| 2 |
1;1;3;3
|
2;1;2;2
| null |
Deep Neural Networks on EEG signals to predict Attention Score using Gramian Angular Difference Field
| null | null | 1.75 | 4.75 |
Withdraw
|
5;5;5;4
|
1;1;1;2
|
null | null |
2022
| 1.666667 | null | null | 0 | null | null | null |
1;2;2
| null | null | null | null | null | 2.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3
|
2;3;3
| null |
Inferring Offensiveness In Images From Natural Language Supervision
| null | null | 2.666667 | 3.333333 |
Reject
|
4;3;3
|
2;3;2
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
3;2;2
| null | null | null |
Uncertainty;Prediction Interval;Regression Uncertainty
| null | 2 | null | null |
iclr
| 0 | 0.866025 | null |
main
| 4.333333 |
3;5;5
|
2;4;3
| null |
Distribution-Driven Disjoint Prediction Intervals for Deep Learning
| null | null | 3 | 3 |
Reject
|
3;4;2
|
2;2;2
|
null |
Google Research
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6254; None
| null | 0 | null | null | null |
1;2;3;4
| null |
Jason Wei, Maarten Bosma, Vincent Zhao, Kelvin Guu, Wei Yu, Brian Lester, Nan Du, Andrew Dai, Quoc V Le
|
https://iclr.cc/virtual/2022/poster/6254
|
natural language processing;zero-shot learning;language models
| null | 3.75 | null |
https://openreview.net/forum?id=gEZrGCozdqR
|
iclr
| 0 | 0 | null |
main
| 8 |
8;8;8;8
|
3;4;4;3
|
https://iclr.cc/virtual/2022/poster/6254
|
Finetuned Language Models are Zero-Shot Learners
| null | null | 3.5 | 4 |
Oral
|
5;3;4;4
|
4;4;3;4
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;3;2
| null | null | null |
lifelong machine learning;data programming;semi-supervised learning
| null | 2.5 | null | null |
iclr
| 0 | 0.707107 | null |
main
| 4 |
3;3;5;5
|
3;2;4;3
| null |
Mako: Semi-supervised continual learning with minimal labeled data via data programming
| null | null | 3 | 4 |
Reject
|
4;4;5;3
|
2;2;3;3
|
null |
Stanford University
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6133; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Lingjiao Chen, Peter Bailis, James Y Zou
|
https://iclr.cc/virtual/2022/poster/6133
|
ML API performance shifts;ML as a service;ML monitoring;ML performance evaluation
| null | 3.5 | null |
https://openreview.net/forum?id=gFDFKC4gHL4
|
iclr
| 0.333333 | 0.333333 | null |
main
| 6.5 |
6;6;6;8
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/6133
|
How Did the Model Change? Efficiently Assessing Machine Learning API Shifts
| null | null | 3.75 | 3.75 |
Poster
|
4;3;4;4
|
4;4;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2;2
| null | null | null | null | null | 2.8 | null | null |
iclr
| -0.133631 | 0.559017 | null |
main
| 5.4 |
3;6;6;6;6
|
2;4;4;2;3
| null |
Post-Training Quantization Is All You Need to Perform Cross-Platform Learned Image Compression
| null | null | 3 | 3.8 |
Reject
|
4;5;4;3;3
|
3;3;3;3;2
|
null |
Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China
|
2022
| 3.5 |
https://iclr.cc/virtual/2022/poster/7058; None
| null | 0 | null | null | null |
3;4;3;4
| null |
Shaojie Li, Yong Liu
|
https://iclr.cc/virtual/2022/poster/7058
| null | null | 1.75 | null |
https://openreview.net/forum?id=gI7feJ9yXPz
|
iclr
| 0.301511 | -0.57735 | null |
main
| 7 |
6;6;8;8
|
3;4;3;3
|
https://iclr.cc/virtual/2022/poster/7058
|
High Probability Generalization Bounds with Fast Rates for Minimax Problems
| null | null | 3.25 | 3.75 |
Poster
|
3;4;5;3
|
3;4;0;0
|
null |
Johns Hopkins University; University of Maryland
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6024; None
| null | 0 | null | null | null |
3;2;3;2
| null |
Renkun Ni, Manli Shu, Hossein Souri, Micah Goldblum, Tom Goldstein
|
https://iclr.cc/virtual/2022/poster/6024
|
meta-learning;contrastive learning;self-supervised learning
| null | 2.75 | null |
https://openreview.net/forum?id=gICys3ITSmj
|
iclr
| 0 | 0.688247 | null |
main
| 5.5 |
5;5;6;6
|
1;3;4;3
|
https://iclr.cc/virtual/2022/poster/6024
|
The Close Relationship Between Contrastive Learning and Meta-Learning
|
https://github.com/RenkunNi/MetaContrastive
| null | 2.75 | 3.5 |
Poster
|
4;3;4;3
|
3;2;3;3
|
null |
Duke University; Illinois Institute of Technology
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6398; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Jinyuan Jia, Binghui Wang, Xiaoyu Cao, Hongbin Liu, Neil Gong
|
https://iclr.cc/virtual/2022/poster/6398
| null | null | 2.75 | null |
https://openreview.net/forum?id=gJLEXy3ySpu
|
iclr
| 0 | 0.333333 | null |
main
| 5.75 |
5;6;6;6
|
3;3;4;3
|
https://iclr.cc/virtual/2022/poster/6398
|
Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations
| null | null | 3.25 | 3 |
Poster
|
3;3;4;2
|
3;3;3;2
|
null |
Department of Computer Science, Brown University
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/5992; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Roma Patel, Ellie Pavlick
|
https://iclr.cc/virtual/2022/poster/5992
| null | null | 3.25 | null |
https://openreview.net/forum?id=gJcEM8sxHK
|
iclr
| -0.777778 | 0.544331 | null |
main
| 6.75 |
5;6;8;8
|
3;2;4;3
|
https://iclr.cc/virtual/2022/poster/5992
|
Mapping Language Models to Grounded Conceptual Spaces
| null | null | 3 | 4.25 |
Poster
|
5;4;4;4
|
4;3;3;3
|
null |
Facebook AI Research; MIT Physics; MIT EECS; MIT CSAIL & BCS; MIT-IBM Watson AI Lab; MIT CSAIL
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/6083; None
| null | 0 | null | null | null |
2;2;2;3
| null |
Rumen R Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic
|
https://iclr.cc/virtual/2022/poster/6083
|
self-supervised learning;contrastive learning;photonics science
| null | 2.5 | null |
https://openreview.net/forum?id=gKLAAfiytI
|
iclr
| -0.174078 | 0.57735 | null |
main
| 6.5 |
6;6;6;8
|
3;4;3;4
|
https://iclr.cc/virtual/2022/poster/6083
|
Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations
|
https://github.com/rdangovs/essl
| null | 3.5 | 3.25 |
Poster
|
4;2;4;3
|
3;2;2;3
|
null | null |
2022
| 3.25 | null | null | 0 | null | null | null |
3;3;4;3
| null | null | null |
logical reasoning;machine reading comprehension;language understanding
| null | 2.5 | null | null |
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
3;4;3;3
| null |
Fact-driven Logical Reasoning
| null | null | 3.25 | 3.5 |
Reject
|
3;4;4;3
|
2;3;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
4;2;2;3
| null | null | null |
No-Free-Lunch Theorems
| null | 0.75 | null | null |
iclr
| -0.707107 | 1 | null |
main
| 3 |
1;3;3;5
|
1;2;2;3
| null |
There are free lunches
| null | null | 2 | 2.5 |
Reject
|
3;3;2;2
|
1;0;0;2
|
null | null |
2022
| 1.5 | null | null | 0 | null | null | null |
1;1;2;2
| null | null | null |
rienforcement learning;neural combinatorial optimization;vehicle routing problem with time windows;attention model
| null | 1.75 | null | null |
iclr
| 0.333333 | -0.333333 | null |
main
| 2.5 |
1;3;3;3
|
3;1;3;3
| null |
Neural Combinatorial Optimization with Reinforcement Learning : Solving theVehicle Routing Problem with Time Windows
| null | null | 2.5 | 4.25 |
Reject
|
4;5;4;4
|
1;2;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
neural processes;bayesian active learning;stochastic process;deep sequence model;epidemic modeling
| null | 2.5 | null | null |
iclr
| -0.57735 | 0.57735 | null |
main
| 5.75 |
5;6;6;6
|
2;3;2;3
| null |
Accelerating Stochastic Simulation with Interactive Neural Processes
| null | null | 2.5 | 3.5 |
Reject
|
4;4;3;3
|
2;2;3;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
2;3;3;3;4
| null | null | null |
Face Identification;Wireframe;Line Drawing;3D Reconstruction
| null | 2.8 | null | null |
iclr
| 0 | 0.912871 | null |
main
| 5 |
3;5;5;6;6
|
2;4;4;4;4
| null |
Neural Face Identification in a 2D Wireframe Projection of a Manifold Object
| null | null | 3.6 | 4 |
Withdraw
|
4;3;5;3;5
|
2;3;2;3;4
|
null |
New York University; Carnegie Mellon University; University of Massachusetts Amherst
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/7050; None
| null | 0 | null | null | null |
2;3;4
| null |
Raphael Meyer, Cameron Musco, Christopher Musco, David Woodruff, Samson Zhou
|
https://iclr.cc/virtual/2022/poster/7050
|
regression;sublinear time algorithm;structured input
| null | 1.666667 | null |
https://openreview.net/forum?id=gNp54NxHUPJ
|
iclr
| 0.866025 | 0 | null |
main
| 8 |
6;8;10
|
4;4;4
|
https://iclr.cc/virtual/2022/poster/7050
|
Fast Regression for Structured Inputs
| null | null | 4 | 3.333333 |
Poster
|
3;3;4
|
0;2;3
|
null |
Computer Science & Engineering, University of Notre Dame; Department of Computer Science, University of Iowa
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6071; None
| null | 0 | null | null | null |
3;3;3
| null |
Zhuoning Yuan, Zhishuai Guo, Nitesh Chawla, Tianbao Yang
|
https://iclr.cc/virtual/2022/poster/6071
|
Compositional Training;Imbalanced Losses;AUC optimization;Deep Learning
| null | 3 | null |
https://openreview.net/forum?id=gPvB4pdu_Z
|
iclr
| 0 | 0 |
www.libauc.org
|
main
| 7.333333 |
6;8;8
|
3;3;3
|
https://iclr.cc/virtual/2022/poster/6071
|
Compositional Training for End-to-End Deep AUC Maximization
|
https://github.com/Optimization-AI/LibAUC
| null | 3 | 3 |
Spotlight
|
3;3;3
|
3;3;3
|
null |
University of Washington; NEC Laboratories America, Inc.; Carnegie Mellon University
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6899; None
| null | 0 | null | null | null |
2;3;2;4
| null |
Zhili Feng, Shaobo Han, Simon Du
|
https://iclr.cc/virtual/2022/poster/6899
|
Representation learning;tensor;statistical learning theory
| null | 2.25 | null |
https://openreview.net/forum?id=gRCCdgpVZf
|
iclr
| -0.939336 | -0.727607 | null |
main
| 5.75 |
3;6;6;8
|
4;4;4;3
|
https://iclr.cc/virtual/2022/poster/6899
|
Provable Adaptation across Multiway Domains via Representation Learning
| null | null | 3.75 | 3.5 |
Poster
|
5;4;3;2
|
2;3;2;2
|
null |
Google LLC; Waymo LLC
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6089; None
| null | 0 | null | null | null |
3;2;3;3
| null |
Zhaoqi Leng, Mingxing Tan, Chenxi Liu, Ekin Cubuk, Jay Shi, Shuyang Cheng, Dragomir Anguelov
|
https://iclr.cc/virtual/2022/poster/6089
|
classification;computer vision;loss
| null | 2.5 | null |
https://openreview.net/forum?id=gSdSJoenupI
|
iclr
| 0.774597 | 0.57735 | null |
main
| 6.5 |
6;6;6;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6089
|
PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions
| null | null | 3.5 | 3.5 |
Poster
|
4;2;3;5
|
3;2;2;3
|
null | null |
2022
| 0 | null | null | 0 | null | null | null | null | null | null | null |
random features;over-parameterized model;double descent;SGD
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 0 | null | null | null |
On the Double Descent of Random Features Models Trained with SGD
| null | null | 0 | 0 |
Desk Reject
| null | null |
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
3;2;2
| null | null | null |
Decision Region;Adversarial Robustness;Deep Neural Networks
| null | 2.333333 | null | null |
iclr
| -0.5 | 0 | null |
main
| 5.666667 |
5;6;6
|
3;3;3
| null |
Empirical Study of the Decision Region and Robustness in Deep Neural Networks
| null | null | 3 | 3.333333 |
Reject
|
4;4;2
|
3;2;2
|
null |
Huawei Noah’s Ark Lab; Zhejiang University
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/7004; None
| null | 0 | null | null | null |
3;3;3
| null |
Yao Zhu, Jiacheng Sun, Zhenguo Li
|
https://iclr.cc/virtual/2022/poster/7004
|
Adversarial Attack;Adversarial Transferability;Black-box Attack
| null | 2.666667 | null |
https://openreview.net/forum?id=gVRhIEajG1k
|
iclr
| 0 | 0 | null |
main
| 7 |
5;8;8
|
3;3;3
|
https://iclr.cc/virtual/2022/poster/7004
|
Rethinking Adversarial Transferability from a Data Distribution Perspective
| null | null | 3 | 4 |
Poster
|
4;4;4
|
3;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Differential Privacy;Federated Learning;Skellam Distribution;Renyi Divergence
| null | 1.75 | null | null |
iclr
| 0 | 0.752618 | null |
main
| 5.5 |
3;5;6;8
|
2;4;3;4
| null |
Distributed Skellam Mechanism: a Novel Approach to Federated Learning with Differential Privacy
| null | null | 3.25 | 4 |
Reject
|
4;4;4;4
|
2;2;3;0
|
null | null |
2022
| 1.25 | null | null | 0 | null | null | null |
1;1;1;2
| null | null | null |
Anomaly detection;attention mechanism;frame-group;spatial-temporal feature
| null | 1.5 | null | null |
iclr
| -0.707107 | 0 | null |
main
| 2 |
1;1;3;3
|
3;2;3;2
| null |
ANOMALY DETECTION WITH FRAME-GROUP ATTENTION IN SURVEILLANCE VIDEOS
| null | null | 2.5 | 4 |
Reject
|
5;4;4;3
|
1;2;1;2
|
null | null |
2022
| 2.6 | null | null | 0 | null | null | null |
3;2;2;3;3
| null | null | null | null | null | 2.6 | null | null |
iclr
| -0.872872 | 0.645497 | null |
main
| 5.4 |
5;5;5;6;6
|
3;3;2;4;3
| null |
Weakly Supervised Graph Clustering
| null | null | 3 | 2.8 |
Reject
|
3;3;4;2;2
|
3;2;2;3;3
|
null |
Sorbonne Université, CNRS, LOCEAN-IPSL, F-75005 Paris, France; Sorbonne Université, CNRS, ISIR, F-75005 Paris, France; Criteo AI Labs, Paris, France; Sorbonne Université, CNRS, ISIR, F-75005 Paris, France
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6791; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Jérémie DONA, Marie Déchelle, patrick gallinari, Marina Levy
|
https://iclr.cc/virtual/2022/poster/6791
|
Deep Learning;Hybrid Models;Differential Equations
| null | 2.5 | null |
https://openreview.net/forum?id=gbe1zHyA73
|
iclr
| 0.70014 | -0.080845 | null |
main
| 5.75 |
3;6;6;8
|
4;4;3;4
|
https://iclr.cc/virtual/2022/poster/6791
|
Constrained Physical-Statistics Models for Dynamical System Identification and Prediction
| null | null | 3.75 | 3.5 |
Poster
|
3;4;3;4
|
2;2;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Adversarial training;Robustness;Overfitting;Neural networks
| null | 2.5 | null | null |
iclr
| 0 | 0.942809 | null |
main
| 6 |
5;5;6;8
|
3;3;3;4
| null |
Towards the Memorization Effect of Neural Networks in Adversarial Training
| null | null | 3.25 | 3.75 |
Reject
|
4;4;3;4
|
2;2;3;3
|
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
1;1;2;3
| null | null | null |
robustness;spurious correlations;feature priors
| null | 2.25 | null | null |
iclr
| 0.544331 | 0.833333 | null |
main
| 5 |
3;3;6;8
|
2;3;3;4
| null |
Combining Diverse Feature Priors
| null | null | 3 | 3.5 |
Reject
|
2;4;4;4
|
2;1;3;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;2;4
| null | null | null |
Equitable and Optimal Transport;Fairness;Saddle Point Problem;Projected Alternating Maximization;Block Coordinate Descent;Acceleration;Rounding
| null | 2 | null | null |
iclr
| 0.132453 | 0.132453 | null |
main
| 6.25 |
5;6;6;8
|
4;3;4;4
| null |
On the Convergence of Projected Alternating Maximization for Equitable and Optimal Transport
| null | null | 3.75 | 3.75 |
Reject
|
4;3;4;4
|
2;1;1;4
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;3;2;2
| null | null | null |
Federated Learning;Neural Tangent Kernel
| null | 2 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5;5
|
3;2;3;3
| null |
Neural Tangent Kernel Empowered Federated Learning
| null | null | 2.75 | 3.5 |
Reject
|
3;4;3;4
|
2;1;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
1;3;3;3;3;2
| null | null | null |
Markov Chain Monte Carlo;Nesterov Accelerated Gradient;accelerated sampling
| null | 2.333333 | null | null |
iclr
| 0.578006 | 0.559017 | null |
main
| 4 |
1;3;3;5;6;6
|
2;4;2;3;4;3
| null |
Hessian-Free High-Resolution Nesterov Acceleration for Sampling
| null | null | 3 | 3.333333 |
Reject
|
1;4;4;4;3;4
|
1;2;2;3;3;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3;3
| null | null | null | null | null | 2.5 | null | null |
iclr
| 0 | 0.418121 | null |
main
| 5.5 |
3;5;6;8
|
2;4;4;3
| null |
Learning Algebraic Representation for Systematic Generalization in Abstract Reasoning
| null | null | 3.25 | 3 |
Withdraw
|
3;3;3;3
|
3;2;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
Reinforcement learning;policy optimization;hinge loss;policy improvement;PPO-clip
| null | 2 | null | null |
iclr
| -0.954427 | 0.800641 | null |
main
| 5.5 |
3;5;6;8
|
3;3;3;4
| null |
Hinge Policy Optimization: Rethinking Policy Improvement and Reinterpreting PPO
| null | null | 3.25 | 3.75 |
Reject
|
5;4;4;2
|
2;2;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;2;3;3
| null | null | null |
Neural network approximation;expressiveness of width bounded neural networks;maximum principle
| null | 1.5 | null | null |
iclr
| -0.57735 | -0.57735 | null |
main
| 5.75 |
5;6;6;6
|
4;3;4;3
| null |
Expressiveness of Neural Networks Having Width Equal or Below the Input Dimension
| null | null | 3.5 | 3.5 |
Reject
|
4;3;3;4
|
3;0;3;0
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
offline reinforcement learning;multi-task reinforcement learning
| null | 2 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5
|
4;3;4
| null |
Data Sharing without Rewards in Multi-Task Offline Reinforcement Learning
| null | null | 3.666667 | 3.333333 |
Reject
|
4;3;3
|
2;2;2
|
null |
Singapore University of Technology and Design; University of California, Irvine
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/7008; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Stefanos Leonardos, Will Overman, Ioannis Panageas, Georgios Piliouras
|
https://iclr.cc/virtual/2022/poster/7008
|
Multi-agent Reinforcement Learning;Markov Potential Games;Policy Gradient
| null | 1.5 | null |
https://openreview.net/forum?id=gfwON7rAm4
|
iclr
| 0.555556 | -0.555556 | null |
main
| 6.75 |
5;6;8;8
|
4;4;4;3
|
https://iclr.cc/virtual/2022/poster/7008
|
Global Convergence of Multi-Agent Policy Gradient in Markov Potential Games
| null | null | 3.75 | 3.25 |
Poster
|
3;3;3;4
|
2;2;0;2
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;2;4
| null | null | null |
meta-SCM;cyclic causal models;sufficient activated mechanisms
| null | 1.666667 | null | null |
iclr
| 0.5 | 0.5 | null |
main
| 4.666667 |
3;3;8
|
4;2;4
| null |
Connecting Data to Mechanisms with Meta Structual Causal Model
| null | null | 3.333333 | 3.666667 |
Reject
|
3;4;4
|
0;1;4
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
feudal reinforcement learning;textual instruction following;reading to act;text games;multi-hop reasoning
| null | 3.25 | null | null |
iclr
| -0.473684 | 0.132453 | null |
main
| 4.75 |
3;5;5;6
|
3;3;4;3
| null |
Feudal Reinforcement Learning by Reading Manuals
| null | null | 3.25 | 3.75 |
Reject
|
5;2;4;4
|
4;3;3;3
|
null | null |
2022
| 2.6 | null | null | 0 | null | null | null |
2;3;3;2;3
| null | null | null |
Machine Learning;Unsupervised Feature Selection;Knowledge Distillation
| null | 2.8 | null | null |
iclr
| -0.800095 | 0 | null |
main
| 5.6 |
3;5;6;6;8
|
3;3;3;3;3
| null |
Second-Order Unsupervised Feature Selection via Knowledge Contrastive Distillation
| null | null | 3 | 4.2 |
Reject
|
5;4;4;4;4
|
2;3;3;3;3
|
null |
Georgia Institute of Technology, Atlanta, GA 30332, USA
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6808; None
| null | 0 | null | null | null |
3;2;4
| null |
Sachin Konan, Esmaeil Seraj, Matthew Gombolay
|
https://iclr.cc/virtual/2022/poster/6808
|
Multi-agent Reinforcement Learning;Cooperation and Coordination;Policy Gradient Optimization;Mutual Information;Iterated Reasoning
| null | 2.666667 | null |
https://openreview.net/forum?id=giBFoa-uS12
|
iclr
| -0.917663 | 0.802955 | null |
main
| 5.666667 |
3;6;8
|
3;3;4
|
https://iclr.cc/virtual/2022/poster/6808
|
Iterated Reasoning with Mutual Information in Cooperative and Byzantine Decentralized Teaming
| null | null | 3.333333 | 3.333333 |
Poster
|
4;3;3
|
2;2;4
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
communication networks;distributed protocols
| null | 1.25 | null | null |
iclr
| -0.738549 | 0.816497 | null |
main
| 6 |
5;5;6;8
|
3;3;4;4
| null |
Mistill: Distilling Distributed Network Protocols from Examples
| null | null | 3.5 | 3.25 |
Reject
|
3;4;4;2
|
2;3;0;0
|
null |
Department of Computer Science & Engineering, Texas A&M University, College Station, TX 77843, USA
|
2022
| 3.333333 |
https://iclr.cc/virtual/2022/poster/6403; None
| null | 0 | null | null | null |
3;3;4
| null |
Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, Shuiwang Ji
|
https://iclr.cc/virtual/2022/poster/6403
| null | null | 3 | null |
https://openreview.net/forum?id=givsRXsOt9r
|
iclr
| -0.5 | 0.5 | null |
main
| 7 |
5;8;8
|
3;4;3
|
https://iclr.cc/virtual/2022/poster/6403
|
Spherical Message Passing for 3D Molecular Graphs
|
https://github.com/divelab/DIG
| null | 3.333333 | 4.333333 |
Poster
|
5;3;5
|
2;3;4
|
null |
NAVER AI Lab; University of Vermont; KAIST; UIUC; Institute for Basic Science
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6012; None
| null | 0 | null | null | null |
2;3;3;4
| null |
Yooju Shin, Susik Yoon, Sundong Kim, Hwanjun Song, Jae-Gil Lee, Byung Suk Lee
|
https://iclr.cc/virtual/2022/poster/6012
|
active learning;time series;pseudo labeling
| null | 3.75 | null |
https://openreview.net/forum?id=gjNcH0hj0LM
|
iclr
| 0.816497 | 0.57735 | null |
main
| 7 |
6;6;6;10
|
3;4;3;4
|
https://iclr.cc/virtual/2022/poster/6012
|
Coherence-based Label Propagation over Time Series for Accelerated Active Learning
| null | null | 3.5 | 3 |
Poster
|
3;3;2;4
|
4;4;3;4
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;4;2
| null | null | null |
Source Extraction;Variational Inference;Disentanglement
| null | 2.5 | null | null |
iclr
| -0.544331 | 0.942809 | null |
main
| 6 |
3;5;8;8
|
3;3;4;4
| null |
Variational Component Decoder for Source Extraction from Nonlinear Mixture
| null | null | 3.5 | 3.5 |
Reject
|
4;4;4;2
|
2;2;3;3
|
null | null |
2022
| 2.666667 |
https://iclr.cc/virtual/2022/poster/6892; None
| null | 0 | null | null | null |
2;2;4
| null |
Yifan Gong, Yuguang Yao, Yize Li, Yimeng Zhang, Xiaoming Liu, Xue Lin, Sijia Liu
|
https://iclr.cc/virtual/2022/poster/6892
|
Reverse Engineering of Deceptions;adversarial examples;denoising;neural networks;interpretability
| null | 3 | null |
https://openreview.net/forum?id=gpp7cf0xdfN
|
iclr
| 0.5 | -0.5 | null |
main
| 6.666667 |
6;6;8
|
4;3;3
|
https://iclr.cc/virtual/2022/poster/6892
|
Reverse Engineering of Imperceptible Adversarial Image Perturbations
| null | null | 3.333333 | 3.333333 |
Poster
|
4;2;4
|
3;2;4
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Semi-supervised Image Captioning;Novel Object Captioning
| null | 2 | null | null |
iclr
| 0 | 0 | null |
main
| 5.75 |
5;6;6;6
|
3;3;3;3
| null |
Learning Visual-Linguistic Adequacy, Fidelity, and Fluency for Novel Object Captioning
| null | null | 3 | 4 |
Reject
|
4;3;4;5
|
2;2;0;4
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
network pruning;structured pruning;dynamical isometry;model compression
| null | 2.25 | null | null |
iclr
| 0 | 0.57735 | null |
main
| 4.5 |
3;3;6;6
|
2;3;3;3
| null |
Structured Pruning Meets Orthogonality
| null | null | 2.75 | 4.5 |
Reject
|
5;4;5;4
|
2;2;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;1;2;3
| null | null | null |
quantization;pruning;bit-wise training;resnet;lenet
| null | 2.25 | null | null |
iclr
| -0.816497 | 0.870388 | null |
main
| 4.25 |
3;3;5;6
|
1;2;3;3
| null |
Bit-wise Training of Neural Network Weights
| null | null | 2.25 | 4 |
Reject
|
4;5;4;3
|
1;2;3;3
|
null |
Paper under double-blind review
|
2022
| 2.75 | null | null | 0 | null | null | null |
3;3;2;3
| null | null | null |
fast adversarial training;bi-level optimization;adversarial robustness;adversarial defense
| null | 2.5 | null | null |
iclr
| 0.132453 | 0.688247 | null |
main
| 4.75 |
3;5;5;6
|
2;2;3;3
| null |
Revisiting and Advancing Fast Adversarial Training Through the lens of Bi-Level Optimization
| null | null | 2.5 | 4.25 |
Reject
|
4;5;4;4
|
2;3;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
Soft Labels;Knowledge distillation
| null | 2.75 | null | null |
iclr
| 0 | 1 | null |
main
| 5.75 |
5;6;6;6
|
2;3;3;3
| null |
Reducing the Teacher-Student Gap via Adaptive Temperatures
| null | null | 2.75 | 4 |
Reject
|
4;4;4;4
|
2;3;3;3
|
null |
KAIST; Rutgers University
|
2022
| 2.333333 |
https://iclr.cc/virtual/2022/poster/6051; None
| null | 0 | null | null | null |
2;3;2
| null |
Gautam Singh, Fei Deng, Sungjin Ahn
|
https://iclr.cc/virtual/2022/poster/6051
|
Zero-Shot Image Generation;Compositional Representation;Object-Centric Representation;Out-of-Distribution Generalization;Image Transformers
| null | 3 | null |
https://openreview.net/forum?id=h0OYV0We3oh
|
iclr
| 0 | 0 |
https://sites.google.com/view/slate-autoencoder
|
main
| 6 |
6;6;6
|
4;3;3
|
https://iclr.cc/virtual/2022/poster/6051
|
Illiterate DALL-E Learns to Compose
|
https://github.com/singhgautam/slate
| null | 3.333333 | 4.333333 |
Poster
|
5;4;4
|
3;3;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;4;2;3
| null | null | null | null | null | 2.75 | null | null |
iclr
| -0.760886 | 0.345857 | null |
main
| 4.75 |
3;5;5;6
|
3;4;2;4
| null |
Diffusion-Based Representation Learning
| null | null | 3.25 | 4.25 |
Reject
|
5;5;4;3
|
3;2;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
Multimodal modeling;self-supervision;metric learning
| null | 2.25 | null | null |
iclr
| -0.707107 | 0.57735 | null |
main
| 4 |
3;3;5;5
|
3;3;4;3
| null |
Refining Multimodal Representations using a modality-centric self-supervised module
| null | null | 3.25 | 4 |
Withdraw
|
4;5;3;4
|
2;2;3;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Disentanglement;explainability;latent representation
| null | 2 | null | null |
iclr
| -0.174078 | 0.57735 | null |
main
| 3.75 |
3;3;3;6
|
3;3;4;4
| null |
Unifying Categorical Models by Explicit Disentanglement of the Labels' Generative Factors
| null | null | 3.5 | 3.25 |
Reject
|
2;4;4;3
|
2;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
| -1 | 1 | null |
main
| 3.75 |
3;3;3;6
|
2;2;2;3
| null |
Towards Human-Understandable Visual Explanations: Human Imperceptible Cues Can Better Be Removed
| null | null | 2.25 | 3.75 |
Withdraw
|
4;4;4;3
|
2;2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
quantization;binary network;low bit network;Straight through estimator;STE
| null | 0.25 | null | null |
iclr
| -0.904534 | -0.707107 | null |
main
| 4 |
3;3;5;5
|
3;4;2;3
| null |
Proper Straight-Through Estimator: Breaking symmetry promotes convergence to true minimum
| null | null | 3 | 3.75 |
Reject
|
4;5;3;3
|
1;0;0;0
|
null |
University of Science and Technology of China; National University of Singapore
|
2022
| 2.666667 |
https://iclr.cc/virtual/2022/poster/6555; None
| null | 0 | null | null | null |
2;3;3
| null |
Ying-Xin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua
|
https://iclr.cc/virtual/2022/poster/6555
|
Interpretability;Graph Neural Networks;Causal Discovery;Invariant Learning
| null | 3 | null |
https://openreview.net/forum?id=hGXij5rfiHw
|
iclr
| -0.5 | 0.5 | null |
main
| 7.333333 |
6;8;8
|
3;3;4
|
https://iclr.cc/virtual/2022/poster/6555
|
Discovering Invariant Rationales for Graph Neural Networks
|
https://github.com/Wuyxin/DIR-GNN
| null | 3.333333 | 3.666667 |
Poster
|
4;3;4
|
2;3;4
|
null |
Under double-blind review
|
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
language modeling;proteins;fitness prediction
| null | 2.25 | null | null |
iclr
| -0.522233 | 0 | null |
main
| 4.25 |
3;3;5;6
|
4;2;3;3
| null |
Don’t throw away that linear head: Few-shot protein fitness prediction with generative models
| null | null | 3 | 4.25 |
Withdraw
|
4;5;5;3
|
1;2;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
Subpopulation shift;Hierarchical;Hierarchical Networks;Conditional Training;Domain Adaptation
| null | 2.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 4.333333 |
3;5;5
|
3;3;3
| null |
Encoding Hierarchical Information in Neural Networks Helps in Subpopulation Shift
| null | null | 3 | 4 |
Reject
|
4;4;4
|
2;3;2
|
null | null |
2022
| 1.25 | null | null | 0 | null | null | null |
2;1;1;1
| null | null | null | null | null | 2.5 | null | null |
iclr
| 0.57735 | 0.816497 | null |
main
| 3.5 |
3;3;3;5
|
3;3;2;4
| null |
Benchmarking Algorithms from Machine Learning for Low-Budget Black-Box Optimization
| null | null | 3 | 3.5 |
Withdraw
|
3;4;3;4
|
2;2;2;4
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null | null | null | 2.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 4.333333 |
3;5;5
|
3;3;3
| null |
Learning Graph Augmentations to Learn Graph Representations
| null | null | 3 | 4 |
Withdraw
|
4;4;4
|
2;2;3
|
null | null |
2022
| 2.428571 | null | null | 0 | null | null | null |
2;2;2;3;2;4;2
| null | null | null |
distribution;time series;classification;multivariate;wavelet;scattering;feature selection;scaling
| null | 2.285714 | null | null |
iclr
| 0.209529 | 0.82885 | null |
main
| 4.428571 |
3;3;3;5;5;6;6
|
2;2;2;2;3;3;3
| null |
Taking ROCKET on an efficiency mission: A distributed solution for fast and accurate multivariate time series classification
| null | null | 2.428571 | 3.714286 |
Reject
|
4;3;4;4;3;4;4
|
2;2;2;3;2;3;2
|
null | null |
2022
| 2.2 | null | null | 0 | null | null | null |
2;2;2;3;2
| null | null | null | null | null | 1.8 | null | null |
iclr
| -0.645497 | 0.666667 | null |
main
| 3.8 |
3;3;3;5;5
|
2;3;2;3;3
| null |
NAS-Bench-Zero: A Large Scale Dataset for Understanding Zero-Shot Neural Architecture Search
| null | null | 2.6 | 4 |
Withdraw
|
4;5;4;3;4
|
2;3;2;0;2
|
null | null |
2022
| 2.2 | null | null | 0 | null | null | null |
2;3;2;2;2
| null | null | null | null | null | 2.6 | null | null |
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6;6
|
4;3;3;4;3
| null |
A Joint Subspace View to Convolutional Neural Networks
| null | null | 3.4 | 4 |
Reject
|
5;3;4;3;5
|
2;3;3;3;2
|
null |
Google AI
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6721; None
| null | 0 | null | null | null |
2;3;3;4
| null |
Behrooz Ghorbani, Orhan Firat, Markus Freitag, Ankur Bapna, Maxim Krikun, Xavier Garcia, Ciprian Chelba, Colin Cherry
|
https://iclr.cc/virtual/2022/poster/6721
|
Scaling Laws;Neural Machine Translation;NMT;Model Scaling
| null | 3.5 | null |
https://openreview.net/forum?id=hR_SMu8cxCV
|
iclr
| 1 | 0 | null |
main
| 8.5 |
8;8;8;10
|
4;4;4;4
|
https://iclr.cc/virtual/2022/poster/6721
|
Scaling Laws for Neural Machine Translation
| null | null | 4 | 4.25 |
Spotlight
|
4;4;4;5
|
4;3;3;4
|
null |
London School of Economics and Political Science, United Kingdom; The Ohio State University, United States; Microsoft Research, China
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6648; None
| null | 0 | null | null | null |
3;3;3
| null |
Boshi Wang, Jialin Yi, Hang Dong, Bo Qiao, Chuan Luo, Qingwei Lin
|
https://iclr.cc/virtual/2022/poster/6648
| null | null | 3.333333 | null |
https://openreview.net/forum?id=hSktDu-h94
|
iclr
| 0 | -0.5 | null |
main
| 6.666667 |
6;6;8
|
4;3;3
|
https://iclr.cc/virtual/2022/poster/6648
|
Automatic Loss Function Search for Predict-Then-Optimize Problems with Strong Ranking Property
| null | null | 3.333333 | 4 |
Poster
|
4;4;4
|
4;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Graph neural networks;Adversarial weight perturbation
| null | 2.5 | null | null |
iclr
| -0.492366 | -0.288675 | null |
main
| 5 |
3;5;6;6
|
3;4;3;2
| null |
Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks
| null | null | 3 | 3.25 |
Reject
|
4;3;4;2
|
2;2;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
imitation learning;offline imitation learning
| null | 2.25 | null | null |
iclr
| 0.662266 | 0.688247 | null |
main
| 4.75 |
3;5;5;6
|
2;3;2;3
| null |
Discriminator-Weighted Offline Imitation Learning from Suboptimal Demonstrations
| null | null | 2.5 | 3.25 |
Reject
|
3;3;3;4
|
2;2;3;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null | null | null | 2.75 | null | null |
iclr
| 0 | 0.57735 | null |
main
| 5.5 |
5;5;6;6
|
4;3;4;4
| null |
Privacy Protected Multi-Domain Collaborative Learning
| null | null | 3.75 | 4 |
Withdraw
|
4;4;4;4
|
3;2;3;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null | null | null | 2 | null | null |
iclr
| 0.188982 | 0 | null |
main
| 4.666667 |
3;5;6
|
3;3;3
| null |
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
| null | null | 3 | 4.333333 |
Reject
|
4;5;4
|
2;1;3
|
null |
Department of Computer Science, Cornell University, Ithaca, NY 14850, USA
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6161; None
| null | 0 | null | null | null |
3;3;3;2
| null |
Varsha Kishore, Xiangyu Chen, Yan Wang, Boyi Li, Kilian Weinberger
|
https://iclr.cc/virtual/2022/poster/6161
| null | null | 2.75 | null |
https://openreview.net/forum?id=hcMvApxGSzZ
|
iclr
| -0.870388 | 0.333333 | null |
main
| 7.25 |
5;8;8;8
|
3;3;4;3
|
https://iclr.cc/virtual/2022/poster/6161
|
Fixed Neural Network Steganography: Train the images, not the network
|
https://github.com/varshakishore/FNNS
| null | 3.25 | 3.75 |
Poster
|
5;4;3;3
|
2;3;3;3
|
null |
CS Department, University of Toronto; IIIS, Tsinghua University; Shanghai Qi Zhi Institute
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6050; None
| null | 0 | null | null | null |
2;3;3;2
| null |
Zihan Zhou, Wei Fu, Bingliang Zhang, Yi Wu
|
https://iclr.cc/virtual/2022/poster/6050
|
diverse behavior;deep reinforcement learning;multi-agent reinforcement learning
| null | 2.75 | null |
https://openreview.net/forum?id=hcQHRHKfN_
|
iclr
| 0.333333 | 1 | null |
main
| 7.25 |
5;8;8;8
|
2;4;4;4
|
https://iclr.cc/virtual/2022/poster/6050
|
Continuously Discovering Novel Strategies via Reward-Switching Policy Optimization
| null | null | 3.5 | 3.25 |
Poster
|
3;3;4;3
|
2;3;3;3
|
null |
Nanyang Technological University; UC Santa Cruz; Johns Hopkins University
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6172; None
| null | 0 | null | null | null |
2;2;3;4
| null |
Jieru Mei, Yucheng Han, Yutong Bai, Yixiao Zhang, Yinigwei Li, xianhang li, Alan Yuille, Cihang Xie
|
https://iclr.cc/virtual/2022/poster/6172
|
Adversarial examples;efficient training;generalization
| null | 2.75 | null |
https://openreview.net/forum?id=hcoswsDHNAW
|
iclr
| 0.57735 | 1 | null |
main
| 6.5 |
5;5;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6172
|
Fast AdvProp
|
https://github.com/meijieru/fast_advprop
| null | 3.5 | 4.25 |
Poster
|
4;4;4;5
|
2;2;3;4
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
1;3;2;3
| null | null | null |
Probability estimation;calibration;uncertainty;weather forecasting;medical prognosis;car crash;benchmark datasets;deep learning;high dimensional data
| null | 2.25 | null | null |
iclr
| -0.526152 | 0.866154 | null |
main
| 4.25 |
1;5;5;6
|
1;3;4;3
| null |
Deep Probability Estimation
| null | null | 2.75 | 3.75 |
Reject
|
4;4;4;3
|
1;3;2;3
|
null |
University of Cambridge; University of Cambridge, Alan Turing Institute
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6509; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Ross Clarke, Elre Oldewage, José Miguel Hernández Lobato
|
https://iclr.cc/virtual/2022/poster/6509
|
Hyperparameter Optimisation
| null | 2.75 | null |
https://openreview.net/forum?id=hfU7Ka5cfrC
|
iclr
| 0.57735 | 1 | null |
main
| 7.5 |
6;8;8;8
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/6509
|
Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation
| null | null | 3.75 | 3.5 |
Spotlight
|
3;3;4;4
|
3;3;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;3;2;2
| null | null | null | null | null | 2 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5;5
|
3;3;3;3
| null |
MCL-GAN: Generative Adversarial Networks with Multiple Specialized Discriminators
| null | null | 3 | 4 |
Withdraw
|
4;4;4;4
|
2;2;2;2
|
null |
Department of Mathematics, Cornell University, Ithaca, NY 14853, USA; Mathematical Institute, University of Oxford, Oxford, OX2 6GG, UK
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/7116; None
| null | 0 | null | null | null |
3;4;2
| null |
Nicolas Boulle, Alex Townsend
|
https://iclr.cc/virtual/2022/poster/7116
|
Low rank approximation;Randomized SVD;Hilbert--Schmidt operators;Gaussian processes
| null | 2.666667 | null |
https://openreview.net/forum?id=hgKtwSb4S2
|
iclr
| 0.5 | 0.5 | null |
main
| 7 |
5;8;8
|
3;4;3
|
https://iclr.cc/virtual/2022/poster/7116
|
A generalization of the randomized singular value decomposition
| null | null | 3.333333 | 3.333333 |
Poster
|
3;4;3
|
2;3;3
|
null |
Department of Computer Science, University of Central Florida; Intel Labs
|
2022
| 2 |
https://iclr.cc/virtual/2022/poster/6498; None
| null | 0 | null | null | null |
2;2;1;3
| null |
Hassam Sheikh, mariano Phielipp, Ladislau Boloni
|
https://iclr.cc/virtual/2022/poster/6498
|
Ensemble Based Reinforcement Learning;Ensemble Diversity
| null | 2.75 | null |
https://openreview.net/forum?id=hjd-kcpDpf2
|
iclr
| -0.57735 | -0.57735 | null |
main
| 5.25 |
3;6;6;6
|
3;2;2;3
|
https://iclr.cc/virtual/2022/poster/6498
|
Maximizing Ensemble Diversity in Deep Reinforcement Learning
| null | null | 2.5 | 3.5 |
Poster
|
4;4;3;3
|
2;3;3;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
interpretability;compression;network training
| null | 2.75 | null | null |
iclr
| -1 | 0 | null |
main
| 5.5 |
5;5;6;6
|
3;3;3;3
| null |
When less is more: Simplifying inputs aids neural network understanding
| null | null | 3 | 3.5 |
Reject
|
4;4;3;3
|
3;2;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null | null | null | 2.5 | null | null |
iclr
| -0.333333 | 0 | null |
main
| 5.75 |
5;6;6;6
|
3;3;3;3
| null |
Clustered Task-Aware Meta-Learning by Learning from Learning Paths
| null | null | 3 | 3.5 |
Reject
|
4;4;4;2
|
3;2;2;3
|
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
1;1;3;2
| null | null | null |
dataset compression;matrix product state
| null | 1.75 | null | null |
iclr
| -0.522233 | 0.738549 | null |
main
| 3.5 |
1;3;5;5
|
1;1;4;2
| null |
Image Dataset Compression Based on Matrix Product States
| null | null | 2 | 3.75 |
Withdraw
|
4;4;3;4
|
1;1;3;2
|
null |
Invenia Labs, Cambridge, UK; Samsung AI Center, Cambridge, UK; Department of Computer Science and Technology, University of Cambridge
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6535; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Shyam Tailor, Felix Opolka, Pietro Lio, Nicholas Lane
|
https://iclr.cc/virtual/2022/poster/6535
|
graph neural networks;efficiency;latency reduction;memory reduction;architecture design;benchmarking;hardware-aware
| null | 2.75 | null |
https://openreview.net/forum?id=hl9ePdHO4_s
|
iclr
| -0.889297 | 0 | null |
main
| 5.75 |
3;6;6;8
|
3;3;3;3
|
https://iclr.cc/virtual/2022/poster/6535
|
Do We Need Anisotropic Graph Neural Networks?
|
https://github.com/shyam196/egc
| null | 3 | 3.25 |
Poster
|
4;3;3;3
|
2;2;3;4
|
null |
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6759; None
| null | 0 | null | null | null |
2;3;4;3
| null |
Keir Adams, Lagnajit Pattanaik, Connor Coley
|
https://iclr.cc/virtual/2022/poster/6759
|
geometric deep learning;equivariance;molecules
| null | 3 | null |
https://openreview.net/forum?id=hm2tNDdgaFK
|
iclr
| 0.544331 | 0.96225 | null |
main
| 6.75 |
5;6;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6759
|
Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations
| null | null | 3.5 | 4 |
Poster
|
4;3;4;5
|
3;3;3;3
|
null |
Department of Control Science and Engineering, Harbin Institute of Technology; Soft Robotics Lab, ETH Zurich
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/7057; None
| null | 0 | null | null | null |
3;3;2;2
| null |
Minghao Han, Jacob Euler-Rolle, Robert Katzschmann
|
https://iclr.cc/virtual/2022/poster/7057
|
Koopman Operator;Robust Control;Robotics;Model Predictive Control;Soft Robotics
| null | 2.5 | null |
https://openreview.net/forum?id=hniLRD_XCA
|
iclr
| 0.258199 | 1 | null |
main
| 6.5 |
6;6;6;8
|
3;3;3;4
|
https://iclr.cc/virtual/2022/poster/7057
|
DeSKO: Stability-Assured Robust Control with a Deep Stochastic Koopman Operator
| null | null | 3.25 | 3.5 |
Poster
|
5;3;2;4
|
2;3;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
Representation learning;temporal knowledge graph completion;knowledge graph embedding;convolutional neural networks
| null | 2.75 | null | null |
iclr
| 1 | 0.333333 | null |
main
| 5.25 |
3;6;6;6
|
3;4;3;3
| null |
TaCE: Time-aware Convolutional Embedding Learning for Temporal Knowledge Graph Completion
| null | null | 3.25 | 3.75 |
Withdraw
|
3;4;4;4
|
2;3;3;3
|
null |
Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6302; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Eli Chien, Chao Pan, Jianhao Peng, Olgica Milenkovic
|
https://iclr.cc/virtual/2022/poster/6302
|
Hypergraph neural networks;multiset functions;deep sets;set transformer
| null | 2.5 | null |
https://openreview.net/forum?id=hpBTIv2uy_E
|
iclr
| -0.301511 | 1 | null |
main
| 7 |
6;6;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6302
|
You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks
|
https://github.com/jianhao2016/AllSet
| null | 3.5 | 3.75 |
Poster
|
5;3;3;4
|
2;2;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Distributed Training;Federated Learning;Gradient Clipping;Communication-Efficient;Optimization
| null | 2 | null | null |
iclr
| -0.132453 | 0.936586 | null |
main
| 4.75 |
3;5;5;6
|
1;4;3;4
| null |
A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks
| null | null | 3 | 3.75 |
Reject
|
4;4;3;4
|
2;2;2;2
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;3;3
| null | null | null |
kernel methods;attention mechanism;theory;exponential families;deformed exponential families
| null | 2 | null | null |
iclr
| 0.188982 | -0.188982 | null |
main
| 4.666667 |
3;5;6
|
4;3;4
| null |
Kernel Deformed Exponential Families for Sparse Continuous Attention
| null | null | 3.666667 | 2.333333 |
Reject
|
2;3;2
|
2;2;2
|
null |
King Abdullah University of Science and Technology, Gaoling School of Artificial Intelligence, Renmin University of China; Harbin Institute of Technology, Peng Cheng Laboratory; Harbin Institute of Technology; Tsinghua University
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/5901; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Xiong Zhou, Xianming Liu, Deming Zhai, Junjun Jiang, Xin Gao, Xiangyang Ji
|
https://iclr.cc/virtual/2022/poster/5901
|
loss function design;margin-based loss;classification
| null | 2.75 | null |
https://openreview.net/forum?id=hqkhcFHOeKD
|
iclr
| 0 | 1 | null |
main
| 7 |
6;6;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/5901
|
Learning Towards The Largest Margins
| null | null | 3.5 | 4 |
Poster
|
4;4;4;4
|
3;2;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;3;2
| null | null | null |
Safe reinforcement learning;safety;Markov games;stochastic games
| null | 1.75 | null | null |
iclr
| -0.333333 | 1 | null |
main
| 3.5 |
3;3;3;5
|
2;2;2;3
| null |
DESTA: A Framework for Safe Reinforcement Learning with Markov Games of Intervention
| null | null | 2.25 | 2.25 |
Reject
|
2;3;2;2
|
2;2;3;0
|
null |
MIT CSAIL; MIT-IBM Watson AI Lab; MIT BCS, CBMM, CSAIL; UIUC
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6120; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Lingjie Mei, Jiayuan Mao, Ziqi Wang, Chuang Gan, Joshua B Tenenbaum
|
https://iclr.cc/virtual/2022/poster/6120
|
Neuro-Symbolic Reasoning;Concept Learning;Meta-Learning
| null | 2.75 | null |
https://openreview.net/forum?id=htWIlvDcY8
|
iclr
| 0.96225 | 0.96225 | null |
main
| 6.75 |
5;6;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6120
|
FALCON: Fast Visual Concept Learning by Integrating Images, Linguistic descriptions, and Conceptual Relations
| null | null | 3.5 | 3.5 |
Poster
|
3;3;4;4
|
2;2;4;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null | null | null | 2 | null | null |
iclr
| 0.288675 | 0.942809 | null |
main
| 6 |
5;5;6;8
|
3;3;3;4
| null |
Distance-Based Background Class Regularization for Open-Set Recognition
| null | null | 3.25 | 4 |
Reject
|
4;3;5;4
|
0;2;3;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;3;2
| null | null | null |
Variational Autoencoders;Latent Space Regularization
| null | 2.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3
|
4;3;2
| null |
Prototypical Variational Autoencoders
| null | null | 3 | 4 |
Withdraw
|
4;4;4
|
2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
POMDP;memory architecture;optimization;reinforcement learning
| null | 2 | null | null |
iclr
| -1 | 0.57735 | null |
main
| 3.5 |
3;3;3;5
|
4;2;2;4
| null |
How memory architecture affects learning in a simple POMDP: the two-hypothesis testing problem
| null | null | 3 | 2.75 |
Reject
|
3;3;3;2
|
2;2;2;2
|
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