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stringclasses 763
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;2;3
| null | null | null |
Hypothesis generation;Edge embedding;Reinforcement learning;Graph walk;Link prediction
| null | 1.75 | null | null |
iclr
| -0.662266 | -0.688247 | null |
main
| 4.75 |
3;5;5;6
|
4;4;3;3
| null |
Explainable Automatic Hypothesis Generation via High-order Graph Walks
| null | null | 3.5 | 3.75 |
Withdraw
|
4;4;4;3
|
0;2;2;3
|
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
| -0.899229 | -0.662266 | null |
main
| 6.25 |
5;6;6;8
|
4;3;3;3
| null |
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests
| null | null | 3.25 | 3.25 |
Reject
|
4;4;3;2
|
2;3;3;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3
| null | null | null |
Machine Learning;Graph Neural Networks
| null | 2.666667 | null | null |
iclr
| 0 | 0.5 | null |
main
| 4 |
3;3;6
|
3;2;3
| null |
Increase and Conquer: Training Graph Neural Networks on Growing Graphs
| null | null | 2.666667 | 4 |
Reject
|
4;4;4
|
2;3;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
3;2;2
| null | null | null | null | null | 2.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5
|
3;3;3
| null |
Learning with Neighbor Consistency for Noisy Labels
| null | null | 3 | 4 |
Withdraw
|
4;4;4
|
2;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
4;2;2;3
| null | null | null |
language modeling;narrative generation;entity memory;dynamic representations
| null | 1.75 | null | null |
iclr
| 0 | -0.333333 | null |
main
| 5.25 |
5;5;5;6
|
4;3;3;3
| null |
Towards Coherent and Consistent Use of Entities in Narrative Generation
| null | null | 3.25 | 4 |
Reject
|
5;3;4;4
|
3;2;2;0
|
null | null |
2022
| 2.2 | null | null | 0 | null | null | null |
2;2;2;2;3
| null | null | null | null | null | 2.6 | null | null |
iclr
| 0.49099 | 0.862582 | null |
main
| 4.8 |
3;3;5;5;8
|
3;2;3;3;4
| null |
Count-GNN: Graph Neural Networks for Subgraph Isomorphism Counting
| null | null | 3 | 3.8 |
Reject
|
4;3;4;4;4
|
3;2;2;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
data imputation;knn;deep learning;artificial neural networks;digital sobriety
| null | 2.666667 | null | null |
iclr
| 0.5 | 1 | null |
main
| 4 |
3;3;6
|
2;2;3
| null |
Tabular Data Imputation: Choose KNN over Deep Learning
| null | null | 2.333333 | 4.666667 |
Reject
|
5;4;5
|
2;3;3
|
null |
Data Platform, Tencent; State Key Lab of CAD & CG, Zhejiang University; School of Software Technology, Zhejiang University; Columbia University
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6267; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Wenxiao Wang, Lu Yao, Long Chen, Binbin Lin, Deng Cai, Xiaofei He, Wei Liu
|
https://iclr.cc/virtual/2022/poster/6267
|
vision transformers;architecture
| null | 2 | null |
https://openreview.net/forum?id=_PHymLIxuI
|
iclr
| -0.688247 | 0 | null |
main
| 6.25 |
5;6;6;8
|
3;3;3;3
|
https://iclr.cc/virtual/2022/poster/6267
|
CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale Attention
|
https://github.com/cheerss/CrossFormer
| null | 3 | 4.5 |
Poster
|
5;4;5;4
|
2;0;3;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;3;3;2
| null | null | null |
Adversarial Attack;Ensemble-based Defence;Model Diversity
| null | 2.25 | null | null |
iclr
| -0.301511 | 1 | null |
main
| 4.5 |
3;3;6;6
|
3;3;4;4
| null |
PARL: Enhancing Diversity of Ensemble Networks to Resist Adversarial Attacks via Pairwise Adversarially Robust Loss Function
| null | null | 3.5 | 4.25 |
Reject
|
4;5;5;3
|
2;2;3;2
|
null |
Department of Electrical and Computer Engineering, University of Texas at Austin; Department of Computer Science and Engineering, Michigan State University
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6081; None
| null | 0 | null | null | null |
3;2;3;3
| null |
Junyuan Hong, Haotao Wang, Zhangyang Wang, Jiayu Zhou
|
https://iclr.cc/virtual/2022/poster/6081
|
federated learning
| null | 2.5 | null |
https://openreview.net/forum?id=_QLmakITKg
|
iclr
| -0.235702 | 0.544331 | null |
main
| 5 |
3;3;6;8
|
2;3;3;3
|
https://iclr.cc/virtual/2022/poster/6081
|
Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization
|
https://github.com/illidanlab/SplitMix
| null | 2.75 | 3.5 |
Poster
|
3;4;4;3
|
2;2;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
Proper Composite Loss;Open Set Recognition in deep learning;Out-of-distribution detection in deep learning
| null | 2 | null | null |
iclr
| -0.522233 | 0.333333 | null |
main
| 3.5 |
3;3;3;5
|
2;3;3;3
| null |
Generalizing Cross Entropy Loss with a Beta Proper Composite Loss: An Improved Loss Function for Open Set Recognition
| null | null | 2.75 | 3.75 |
Withdraw
|
5;4;3;3
|
2;2;2;2
|
null | null |
2022
| 1.5 |
https://iclr.cc/virtual/2022/poster/6275; None
| null | 0 | null | null | null |
2;2;1;1
| null |
Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto
|
https://iclr.cc/virtual/2022/poster/6275
|
Image-based RL;Data augmentation in RL;Continuous Control
| null | 2.5 | null |
https://openreview.net/forum?id=_SJ-_yyes8
|
iclr
| -0.555556 | 0.83887 | null |
main
| 6.75 |
5;6;8;8
|
1;3;4;3
|
https://iclr.cc/virtual/2022/poster/6275
|
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning
| null | null | 2.75 | 4.5 |
Poster
|
5;5;3;5
|
2;2;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
$\ell^{0}$-Sparse Subspace Clustering;Dimensionality Reduction
| null | 2.75 | null | null |
iclr
| 0.816497 | 0.57735 | null |
main
| 5.25 |
5;5;5;6
|
3;3;4;4
| null |
Noisy $\ell^{0}$-Sparse Subspace Clustering on Dimensionality Reduced Data
| null | null | 3.5 | 4 |
Withdraw
|
3;4;4;5
|
3;2;3;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;3;2
| null | null | null |
hierarchical time series;deep learning
| null | 2.666667 | null | null |
iclr
| -0.866025 | 0 | null |
main
| 5.666667 |
5;6;6
|
3;3;3
| null |
Hierarchically Regularized Deep Forecasting
| null | null | 3 | 4 |
Reject
|
5;3;4
|
2;3;3
|
null |
School of Computing, KAIST, Daejeon, 34141, Republic of Korea; Intelligent Robotics Research Division, ETRI, Daejeon 34129, Republic of Korea
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6520; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Khang Truong Giang, Soohwan Song, Sungho Jo
|
https://iclr.cc/virtual/2022/poster/6520
|
multi-view stereo;3D reconstruction;dynamic scale
| null | 1.75 | null |
https://openreview.net/forum?id=_Wzj0J2xs2D
|
iclr
| 0.904534 | 0 | null |
main
| 7 |
6;6;8;8
|
3;4;4;3
|
https://iclr.cc/virtual/2022/poster/6520
|
CURVATURE-GUIDED DYNAMIC SCALE NETWORKS FOR MULTI-VIEW STEREO
| null | null | 3.5 | 3.75 |
Poster
|
3;3;5;4
|
3;2;2;0
|
null |
Department of Computer Science and Technology, Tsinghua University; Yanqi Lake Beijing Institute of Mathematical Sciences and Applications; Yau Mathematical Sciences Center, Tsinghua University
|
2022
| 3.333333 |
https://iclr.cc/virtual/2022/poster/5953; None
| null | 0 | null | null | null |
3;3;4
| null |
Fuchao Wei, Chenglong Bao, Yang Liu
|
https://iclr.cc/virtual/2022/poster/5953
|
Anderson mixing;sequence acceleration;fixed-point iteration;nonconvex optimization;stochastic optimization
| null | 2 | null |
https://openreview.net/forum?id=_X90SIKbHa
|
iclr
| -1 | 0 | null |
main
| 6.666667 |
6;6;8
|
3;3;3
|
https://iclr.cc/virtual/2022/poster/5953
|
A Class of Short-term Recurrence Anderson Mixing Methods and Their Applications
| null | null | 3 | 2.666667 |
Poster
|
3;3;2
|
0;3;3
|
null |
University of Electronic Science and Technology of China, Shenzhen Institute for Advanced Study, UESTC; University of Electronic Science and Technology of China, Shenzhen Institute for Advanced Study, UESTC, Peng Cheng Laboratory; Peking University; Yale University
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6033; None
| null | 0 | null | null | null |
3;2;3;3
| null |
Shikuang Deng, Yuhang Li, Shanghang Zhang, Shi Gu
|
https://iclr.cc/virtual/2022/poster/6033
|
Spiking Neural Networks;Direct Training;Surrogate Gradient;Generalizability
| null | 1.75 | null |
https://openreview.net/forum?id=_XNtisL32jv
|
iclr
| -0.57735 | 0.57735 | null |
main
| 6.5 |
5;5;8;8
|
3;1;3;3
|
https://iclr.cc/virtual/2022/poster/6033
|
Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting
|
https://github.com/Gus-Lab/temporal_efficient_training
| null | 2.5 | 4.25 |
Poster
|
4;5;4;4
|
2;1;1;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;2;3
| null | null | null |
Wasserstein autoencoder;contrastive learning
| null | 2.333333 | null | null |
iclr
| 0.5 | 0.5 | null |
main
| 5.333333 |
5;5;6
|
4;3;4
| null |
Momentum Contrastive Autoencoder: Using Contrastive Learning for Latent Space Distribution Matching in WAE
| null | null | 3.666667 | 3.666667 |
Reject
|
3;4;4
|
3;2;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
Structural Optimization;Graph Classification;Encoding Tree Kernel;Encoding Tree Learning
| null | 2.25 | null | null |
iclr
| -0.57735 | 0.57735 | null |
main
| 3.75 |
3;3;3;6
|
3;2;2;3
| null |
Structural Optimization Makes Graph Classification Simpler and Better
| null | null | 2.5 | 3.5 |
Withdraw
|
4;4;3;3
|
2;2;2;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
4;2;3
| null | null | null |
structured pruning
| null | 2.666667 | null | null |
iclr
| -0.866025 | 0 | null |
main
| 5.666667 |
5;6;6
|
3;3;3
| null |
Feature Flow Regularization: Improving Structured Sparsity in Deep Neural Networks
| null | null | 3 | 4 |
Reject
|
5;3;4
|
3;3;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
Few-shot learning;Robustness;Image Classification
| null | 2 | null | null |
iclr
| 0.5 | 1 | null |
main
| 5.333333 |
5;5;6
|
3;3;4
| null |
A Simple Approach to Adversarial Robustness in Few-shot Image Classification
| null | null | 3.333333 | 3.333333 |
Reject
|
2;4;4
|
2;1;3
|
null | null |
2022
| 1.8 | null | null | 0 | null | null | null |
1;2;2;2;2
| null | null | null |
Neural Network;CNN;LSTM;Unsupervised learning;Denoising;FIB-SEM
| null | 1.8 | null | null |
iclr
| -0.218218 | 0.612372 | null |
main
| 4.2 |
3;3;5;5;5
|
3;2;3;3;3
| null |
Noise Reconstruction and Removal Network: A New Way to Denoise FIB-SEM Images
| null | null | 2.8 | 3.8 |
Reject
|
5;3;3;4;4
|
1;2;2;2;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null | null | null | 1.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5
|
3;3;3
| null |
RNAS: Robust Network Architecture Search beyond DARTS
| null | null | 3 | 3.333333 |
Withdraw
|
4;2;4
|
0;2;2
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
2;3;4;3
| null | null | null |
Causal Representation;Mutual Information;Robust Representation
| null | 3 | null | null |
iclr
| -0.4842 | 0.899229 | null |
main
| 4.75 |
3;5;5;6
|
2;3;4;4
| null |
Informative Robust Causal Representation for Generalizable Deep Learning
| null | null | 3.25 | 3.25 |
Withdraw
|
4;4;2;3
|
2;3;4;3
|
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
1;2;2;2
| null | null | null |
Lottery Ticket Hypothesis;Tabular;Pruning
| null | 1.5 | null | null |
iclr
| -0.426401 | 0.5 | null |
main
| 3 |
1;3;3;5
|
3;2;3;4
| null |
Lottery Ticket Structured Node Pruning for Tabular Datasets
| null | null | 3 | 3.75 |
Reject
|
5;3;3;4
|
1;1;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null | null | null | 2.5 | null | null |
iclr
| -0.333333 | 0 | null |
main
| 5.75 |
5;5;5;8
|
2;3;4;3
| null |
Stabilized Likelihood-based Imitation Learning via Denoising Continuous Normalizing Flow
| null | null | 3 | 4.25 |
Reject
|
5;4;4;4
|
2;3;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
transfer learning;distillation;pretraining;model merging
| null | 2.5 | null | null |
iclr
| 0 | 0 | null |
main
| 4.5 |
3;5;5;5
|
3;3;3;3
| null |
Representation Consolidation from Multiple Expert Teachers
| null | null | 3 | 4 |
Reject
|
4;4;4;4
|
3;3;2;2
|
null | null |
2022
| 1 | null | null | 0 | null | null | null |
1;1;1;1
| null | null | null |
pruning;neural networks;computations;latency;imagenet
| null | 1.5 | null | null |
iclr
| 0 | 0.774597 | null |
main
| 2.5 |
1;3;3;3
|
1;2;3;4
| null |
Pruning Compact ConvNets For Efficient Inference
| null | null | 2.5 | 4 |
Reject
|
4;4;4;4
|
1;2;0;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
neural networks;training;condensation dynamics;implicit regularization
| null | 2.25 | null | null |
iclr
| 0.57735 | 0.57735 | null |
main
| 5.5 |
5;5;6;6
|
3;3;3;4
| null |
Towards Understanding the Condensation of Neural Networks at Initial Training
| null | null | 3.25 | 2.75 |
Reject
|
3;2;3;3
|
2;2;2;3
|
null |
Blavatnik School of Computer Science, Tel Aviv University
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/7127; None
| null | 0 | null | null | null |
2;2;3;3
| null |
Tom Shenkar, Lior Wolf
|
https://iclr.cc/virtual/2022/poster/7127
|
Anomaly detection;Tabular data
| null | 3.25 | null |
https://openreview.net/forum?id=_hszZbt46bT
|
iclr
| 0 | 1 | null |
main
| 7 |
6;6;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/7127
|
Anomaly Detection for Tabular Data with Internal Contrastive Learning
| null | null | 3.5 | 4 |
Poster
|
4;4;4;4
|
3;3;4;3
|
null |
Paper under double-blind review
|
2022
| 2.75 | null | null | 0 | null | null | null |
3;2;3;3
| null | null | null |
Domain transferability;model regularization
| null | 2.75 | null | null |
iclr
| 0.19245 | 0.555556 | null |
main
| 4.25 |
3;3;5;6
|
3;2;3;3
| null |
Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization
| null | null | 2.75 | 3.5 |
Reject
|
3;4;3;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 | 2.25 | null | null |
iclr
| 0 | -0.522233 | null |
main
| 3.5 |
3;3;3;5
|
3;2;4;2
| null |
3D Meta-Registration: Meta-learning 3D Point Cloud Registration Functions
| null | null | 2.75 | 4 |
Reject
|
4;4;4;4
|
3;2;2;2
|
null |
University of California, Los Angeles; Huawei Noah’s Ark Lab; National University of Singapore; The Chinese University of Hong Kong
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6058; None
| null | 0 | null | null | null |
3;3;2;2
| null |
Shoukang Hu, Ruochen Wang, Lanqing HONG, Zhenguo Li, Cho-Jui Hsieh, Jiashi Feng
|
https://iclr.cc/virtual/2022/poster/6058
| null | null | 3 | null |
https://openreview.net/forum?id=_jMtny3sMKU
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
4;3;3;4
|
https://iclr.cc/virtual/2022/poster/6058
|
Generalizing Few-Shot NAS with Gradient Matching
|
https://github.com/skhu101/GM-NAS
| null | 3.5 | 3.5 |
Poster
|
4;4;3;3
|
3;3;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
imitation learning;causal inference;reinforcement learning
| null | 2.25 | null | null |
iclr
| 0.333333 | 0.96225 | null |
main
| 4.25 |
3;3;5;6
|
2;2;3;3
| null |
What Would the Expert $do(\cdot)$?: Causal Imitation Learning
| null | null | 2.5 | 3.25 |
Reject
|
3;3;4;3
|
2;2;2;3
|
null |
University of California, Berkeley
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/7128; None
| null | 0 | null | null | null |
3;3;3;4
| null |
Cassidy Laidlaw, Anca Dragan
|
https://iclr.cc/virtual/2022/poster/7128
|
human model;boltzmann rationality;suboptimality;HRI;human-robot collaboration;generative models;reinforcement learning;deep RL
| null | 3 | null |
https://openreview.net/forum?id=_l_QjPGN5ye
|
iclr
| 0.174078 | 0 | null |
main
| 7.5 |
6;8;8;8
|
4;4;4;4
|
https://iclr.cc/virtual/2022/poster/7128
|
The Boltzmann Policy Distribution: Accounting for Systematic Suboptimality in Human Models
|
https://github.com/cassidylaidlaw/boltzmann-policy-distribution
| null | 4 | 3.25 |
Poster
|
3;4;2;4
|
3;3;2;4
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;2;3
| null | null | null |
transferability;supervised learning;MLP projector
| null | 2.25 | null | null |
iclr
| -0.555556 | 0.816497 | null |
main
| 4.25 |
3;3;5;6
|
3;2;3;4
| null |
Improving the Transferability of Supervised Pretraining with an MLP Projector
| null | null | 3 | 4.25 |
Withdraw
|
5;4;4;4
|
1;2;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;1;3;3
| null | null | null |
explainable ai;deep learning
| null | 2 | null | null |
iclr
| 0.366508 | 0 | null |
main
| 4.75 |
3;3;5;8
|
2;4;3;3
| null |
On the Evolution of Neuron Communities in a Deep Learning Architecture
| null | null | 3 | 3.5 |
Reject
|
3;4;3;4
|
1;2;3;2
|
null |
Paper under double-blind review
|
2022
| 2.5 | null | null | 0 | null | null | null |
3;2;2;3
| null | null | null |
abstractive summarization;content hallucinations
| null | 1.75 | null | null |
iclr
| -0.333333 | 0 | null |
main
| 3.5 |
3;3;3;5
|
3;3;3;3
| null |
MoFE: Mixture of Factual Experts for Controlling Hallucinations in Abstractive Summarization
| null | null | 3 | 4.25 |
Withdraw
|
4;5;4;4
|
2;0;2;3
|
null |
Center for Machine Learning, Georgia Institute of Technology; School of Aerospace Engineering, Georgia Institute of Technology
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/7195; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Qinsheng Zhang, Yongxin Chen
|
https://iclr.cc/virtual/2022/poster/7195
|
Sampling;Path Integral;Stochastic Differential Equation;MCMC
| null | 2.75 | null |
https://openreview.net/forum?id=_uCb2ynRu7Y
|
iclr
| -0.058026 | 0.96225 | null |
main
| 6.75 |
5;6;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/7195
|
Path Integral Sampler: A Stochastic Control Approach For Sampling
| null | null | 3.5 | 3.75 |
Poster
|
3;5;4;3
|
2;3;3;3
|
null | null |
2022
| 1.5 | null | null | 0 | null | null | null |
1;2;2;1
| null | null | null |
scaling;scale;law;laws;few-shot;one-shot;out-of-distribution;ood;generalization;image;vision
| null | 2 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3;3
|
2;3;2;3
| null |
Scaling Laws for the Few-Shot Adaptation of Pre-trained Image Classifiers
| null | null | 2.5 | 4 |
Withdraw
|
4;4;4;4
|
1;2;3;2
|
null |
University of Amsterdam, Johannes Kepler University Linz; University of Amsterdam; UvA-Bosch DeltaLab, University of Amsterdam
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6225; None
| null | 0 | null | null | null |
3;3;4;2;2;4
| null |
Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik Bekkers, Max Welling
|
https://iclr.cc/virtual/2022/poster/6225
|
equivariant graph neural networks;steerable message passing;non-linear convolutions;molecular modeling;covariant information
| null | 3 | null |
https://openreview.net/forum?id=_xwr8gOBeV1
|
iclr
| 0.87831 | 0.46291 | null |
main
| 7 |
6;6;6;6;8;10
|
3;3;4;4;4;4
|
https://iclr.cc/virtual/2022/poster/6225
|
Geometric and Physical Quantities improve E(3) Equivariant Message Passing
| null | null | 3.666667 | 3.666667 |
Spotlight
|
3;3;3;4;4;5
|
3;3;4;2;2;4
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
1;4;2;3
| null | null | null |
Offline Reinforcement Learning;Reinforcement Learning;Transfer Learning;Knowledge Transfer;Resource Constraints
| null | 3 | null | null |
iclr
| -0.174078 | 0.333333 | null |
main
| 5.25 |
5;5;5;6
|
4;3;4;4
| null |
Offline Reinforcement Learning with Resource Constrained Online Deployment
| null | null | 3.75 | 3.25 |
Reject
|
2;4;4;3
|
3;4;3;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;3;2;2
| null | null | null |
Fairness;Recommender systems
| null | 2.25 | null | null |
iclr
| 0.408248 | -0.408248 | null |
main
| 5 |
3;5;6;6
|
4;3;3;4
| null |
Equal Experience in Recommender Systems
| null | null | 3.5 | 3.5 |
Reject
|
3;4;3;4
|
2;3;2;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;1;3
| null | null | null |
Efficient Inference;Deep Neural Networks
| null | 1.25 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3;3
|
2;2;2;2
| null |
BLUnet: Arithmetic-free Inference with Bit-serialised Table Lookup Operation for Efficient Deep Neural Networks
| null | null | 2 | 4 |
Withdraw
|
4;3;5;4
|
2;2;1;0
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;2;4
| null | null | null |
convex optimization;min-max games;saddle-point problems;first-order stochastic methods;proximal methods;operator splitting
| null | 3 | null | null |
iclr
| 0 | -1 | null |
main
| 5.333333 |
5;5;6
|
4;4;3
| null |
Stochastic Projective Splitting: Solving Saddle-Point Problems with Multiple Regularizers
| null | null | 3.666667 | 4 |
Reject
|
4;4;4
|
2;3;4
|
null | null |
2022
| 2.6 | null | null | 0 | null | null | null |
3;2;3;3;2
| null | null | null |
Neural networks;Classification;Data augmentation;Optimal Transport
| null | 2.2 | null | null |
iclr
| -0.77407 | -0.118217 | null |
main
| 4.6 |
3;3;5;6;6
|
4;3;2;4;3
| null |
$k$-Mixup Regularization for Deep Learning via Optimal Transport
| null | null | 3.2 | 3.4 |
Reject
|
4;4;4;2;3
|
2;3;2;2;2
|
null |
Centre Sciences des Données, École normale supérieure PSL, Paris, 75005, France; School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Computer Science Department, Stanford University, Stanford, CA 94305, USA
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6425; None
| null | 0 | null | null | null |
3;2;3;3
| null |
Paul Michel, Tatsunori Hashimoto, Graham Neubig
|
https://iclr.cc/virtual/2022/poster/6425
|
distributionally robust optimization;fairness;deep learning;robustness;adversarial learning
| null | 3 | null |
https://openreview.net/forum?id=a34GrNaYEcS
|
iclr
| 0.57735 | 1 | null |
main
| 7 |
6;6;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6425
|
Distributionally Robust Models with Parametric Likelihood Ratios
|
https://github.com/pmichel31415/P-DRO
| null | 3.5 | 3.25 |
Poster
|
3;3;3;4
|
3;3;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Robotic Grasping;Equivariance;Reinforcement Leanring
| null | 2.5 | null | null |
iclr
| -0.927173 | 0.648886 | null |
main
| 4.75 |
3;5;5;6
|
2;4;3;3
| null |
Equivariant Grasp learning In Real Time
| null | null | 3 | 4.25 |
Withdraw
|
5;4;4;4
|
2;2;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
interpretability;adversarial attack
| null | 2 | null | null |
iclr
| 0 | 0.57735 | null |
main
| 4.5 |
3;5;5;5
|
2;3;3;2
| null |
Brittle interpretations: The Vulnerability of TCAV and Other Concept-based Explainability Tools to Adversarial Attack
| null | null | 2.5 | 4 |
Reject
|
4;4;4;4
|
2;2;2;2
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
2;3;3;4
| null | null | null | null | null | 1.25 | null | null |
iclr
| -0.899229 | 0.927173 | null |
main
| 6.25 |
5;6;6;8
|
3;3;3;4
| null |
Faster No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium
| null | null | 3.25 | 3.25 |
Reject
|
4;4;3;2
|
0;3;2;0
|
null | null |
2022
| 2.4 | null | null | 0 | null | null | null |
2;2;3;2;3
| null | null | null |
differential entropy estimation;differential entropy;mutual information;kernel estimation
| null | 2.8 | null | null |
iclr
| -0.612372 | 0.166667 | null |
main
| 5.6 |
5;5;6;6;6
|
4;3;4;3;4
| null |
KNIFE: Kernelized-Neural Differential Entropy Estimation
| null | null | 3.6 | 3.4 |
Reject
|
5;3;3;3;3
|
3;2;3;3;3
|
null | null |
2022
| 2.2 | null | null | 0 | null | null | null |
1;3;2;2;3
| null | null | null |
network embedding;hypergraph embedding;hyperedge classification;multi-level hypergraph embedding
| null | 2.2 | null | null |
iclr
| -0.285714 | 0 | null |
main
| 3.4 |
1;3;3;5;5
|
3;2;4;3;3
| null |
MULTI-LEVEL APPROACH TO ACCURATE AND SCALABLE HYPERGRAPH EMBEDDING
| null | null | 3 | 3.8 |
Withdraw
|
4;3;5;4;3
|
1;3;2;2;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
2;3;3;4
| null | null | null |
Deep generative models;multimodal learning
| null | 2.5 | null | null |
iclr
| -0.588348 | 0.392232 | null |
main
| 5.5 |
3;5;6;8
|
2;4;3;3
| null |
Scalable multimodal variational autoencoders with surrogate joint posterior
| null | null | 3 | 3 |
Reject
|
3;4;3;2
|
3;2;2;3
|
null | null |
2022
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Non-convex optimization;Gradient Perturbation;Differentially Private Learning;Adaptive Gradient Methods;Stochastic Gradient Descent;Theory
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 0 | null | null | null |
Adaptive Differentially Private Empirical Risk Minimization
| null | null | 0 | 0 |
Withdraw
| null | null |
null |
Huawei Noah’s Ark Lab; School of Life Sciences, IDG/McGovern Institute for Brain Research, Tsinghua University; Gaoling School of AI, Renmin University of China; Dept. of Comp. Sci. & Tech., Institute for AI, BNRist Center, THBI Lab, Tsinghua University
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/5928; None
| null | 0 | null | null | null |
1;4;2;3
| null |
Liyuan Wang, Xingxing Zhang, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing HONG, Shifeng Zhang, Zhenguo Li, Yi Zhong, Jun Zhu
|
https://iclr.cc/virtual/2022/poster/5928
|
Continual Learning;Memory Replay;Data Compression
| null | 2.5 | null |
https://openreview.net/forum?id=a7H7OucbWaU
|
iclr
| 0 | -1 | null |
main
| 5.25 |
3;6;6;6
|
4;3;3;3
|
https://iclr.cc/virtual/2022/poster/5928
|
Memory Replay with Data Compression for Continual Learning
| null | null | 3.25 | 4 |
Poster
|
4;4;4;4
|
2;3;2;3
|
null | null |
2022
| 2.2 | null | null | 0 | null | null | null |
2;1;2;3;3
| null | null | null |
hyperparameter optimization
| null | 2.4 | null | null |
iclr
| -0.884652 | 0.884652 | null |
main
| 4.6 |
3;3;5;6;6
|
2;1;3;3;3
| null |
Dynamic and Efficient Gray-Box Hyperparameter Optimization for Deep Learning
| null | null | 2.4 | 3.6 |
Reject
|
5;4;3;3;3
|
2;1;3;3;3
|
null |
University of Alberta, Amii; Microsoft Research NYC; Google Research; Technion, Israel
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6402; None
| null | 0 | null | null | null |
1;2;4;3
| null |
Manan Tomar, Lior Shani, Yonathan Efroni, Mohammad Ghavamzadeh
|
https://iclr.cc/virtual/2022/poster/6402
|
Reinforcement Learning;Policy Optimization
| null | 3 | null |
https://openreview.net/forum?id=aBO5SvgSt1
|
iclr
| -0.688247 | 0.688247 | null |
main
| 6.25 |
5;6;6;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6402
|
Mirror Descent Policy Optimization
| null | null | 3.5 | 3 |
Poster
|
4;2;4;2
|
2;3;4;3
|
null |
CEA Saclay, Gif-sur-Yvette, France; LTCI, Télémécom Paris, Institut Polytechnique de Paris, Palaiseau, France
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6592; None
| null | 0 | null | null | null |
2;3;2;3
| null |
Mohammad Fahes, Christophe Kervazo, Jerome Bobin, Florence Tupin
|
https://iclr.cc/virtual/2022/poster/6592
|
Algorithm Unrolling/Unfolding;Blind Source Separation;Sparse Representations;Multi-Convex Optimization;Hyper-parameter Choice
| null | 2.25 | null |
https://openreview.net/forum?id=aBVxf5NaaRt
|
iclr
| 0.777778 | 0.816497 | null |
main
| 6.75 |
5;6;8;8
|
2;3;3;4
|
https://iclr.cc/virtual/2022/poster/6592
|
Unrolling PALM for Sparse Semi-Blind Source Separation
| null | null | 3 | 3.5 |
Poster
|
2;4;4;4
|
2;2;2;3
|
null |
University of Washington, Pacific Northwest National Laboratory; Pacific Northwest National Laboratory, University of Washington
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/6976; None
| null | 0 | null | null | null |
3;4;2;4
| null |
Nico Courts, Henry Kvinge
|
https://iclr.cc/virtual/2022/poster/6976
|
generative models;applications of topology to deep learning;many-to-one maps;invertible neural nets
| null | 2.25 | null |
https://openreview.net/forum?id=aBXzcPPOuX
|
iclr
| -0.333333 | 0.333333 | null |
main
| 6.5 |
6;6;6;8
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/6976
|
Bundle Networks: Fiber Bundles, Local Trivializations, and a Generative Approach to Exploring Many-to-one Maps
| null | null | 3.75 | 3.25 |
Poster
|
3;3;4;3
|
3;0;3;3
|
null |
Stanford University; Carnegie Mellon University
|
2022
| 2.333333 |
https://iclr.cc/virtual/2022/poster/6268; None
| null | 0 | null | null | null |
2;3;2
| null |
Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Junyan Zhu, Stefano Ermon
|
https://iclr.cc/virtual/2022/poster/6268
| null | null | 2.333333 | null |
https://openreview.net/forum?id=aBsCjcPu_tE
|
iclr
| 0.866025 | 0.866025 | null |
main
| 6.666667 |
6;6;8
|
2;3;4
|
https://iclr.cc/virtual/2022/poster/6268
|
SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations
| null | null | 3 | 3 |
Poster
|
2;3;4
|
2;2;3
|
null |
Google Research
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/7059; None
| null | 0 | null | null | null |
3;3;4;3
| null |
Thomas Kipf, Gamaleldin Elsayed, Aravindh Mahendran, Austin Stone, Sara Sabour, Georg Heigold, Rico Jonschkowski, Alexey Dosovitskiy, Klaus Greff
|
https://iclr.cc/virtual/2022/poster/7059
| null | null | 3.25 | null |
https://openreview.net/forum?id=aD7uesX1GF_
|
iclr
| 0.301511 | 0.57735 |
https://slot-attention-video.github.io/
|
main
| 7 |
6;6;8;8
|
4;3;4;4
|
https://iclr.cc/virtual/2022/poster/7059
|
Conditional Object-Centric Learning from Video
| null | null | 3.75 | 4.25 |
Poster
|
5;3;5;4
|
3;3;4;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;3;2;3
| null | null | null |
randomized smoothing;certifiable robustness;deep learning;machine learning
| null | 1.5 | null | null |
iclr
| 0.080845 | 0.080845 | null |
main
| 5.25 |
3;5;5;8
|
4;3;4;4
| null |
Intriguing Properties of Input-dependent Randomized Smoothing
| null | null | 3.75 | 3.5 |
Reject
|
4;2;4;4
|
1;1;1;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Bayesian;Probabilistic approaches;MCMC;Hunt Crossley;parameter identification.
| null | 2 | null | null |
iclr
| -0.5 | 0 | null |
main
| 3 |
1;3;3;5
|
3;2;1;3
| null |
ARMCMC: Online Bayesian Density Estimation of Model Parameters
| null | null | 2.25 | 4 |
Withdraw
|
4;5;4;3
|
2;2;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;3;3;2
| null | null | null |
unsupervised learning;representation learning;neurosymbolic program synthesis
| null | 1.75 | null | null |
iclr
| 1 | 0.57735 | null |
main
| 5.25 |
5;5;5;6
|
3;3;4;4
| null |
Unsupervised Learning of Neurosymbolic Encoders
| null | null | 3.5 | 3.25 |
Reject
|
3;3;3;4
|
2;3;2;0
|
null |
Paper under double-blind review
|
2022
| 2.666667 | null | null | 0 | null | null | null |
2;3;3
| null | null | null |
backdoor attacks;deep learning security;pre-trained models
| null | 2 | null | null |
iclr
| 0.114708 | 0.993399 | null |
main
| 5.333333 |
3;5;8
|
2;3;4
| null |
Gradient Broadcast Adaptation: Defending against the backdoor attack in pre-trained models
| null | null | 3 | 3.666667 |
Reject
|
4;3;4
|
1;2;3
|
null | null |
2022
| 1.5 | null | null | 0 | null | null | null |
1;1;1;3
| null | null | null |
Reinforcement Learning;Batch RL;Online RL;Offline RL
| null | 2.25 | null | null |
iclr
| -0.57735 | 0 | null |
main
| 4 |
3;3;5;5
|
3;4;3;4
| null |
Offline-Online Reinforcement Learning: Extending Batch and Online RL
| null | null | 3.5 | 3.5 |
Reject
|
3;5;3;3
|
2;2;2;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;2;3
| null | null | null |
Controllable sequence models;Text to speech;Text to handwriting
| null | 3 | null | null |
iclr
| 0 | 0.993399 | null |
main
| 5.666667 |
3;6;8
|
2;3;4
| null |
Style Equalization: Unsupervised Learning of Controllable Generative Sequence Models
| null | null | 3 | 4 |
Reject
|
4;4;4
|
2;3;4
|
null | null |
2022
| 1.5 | null | null | 0 | null | null | null |
1;2;1;2
| null | null | null |
Continual Learning;robust experimental protocol;task oracle;task identifier
| null | 2 | null | null |
iclr
| 0.40452 | 0.852803 | null |
main
| 3.5 |
1;3;5;5
|
2;3;4;3
| null |
Design and Evaluation for Robust Continual Learning
| null | null | 3 | 3.5 |
Reject
|
2;5;4;3
|
2;2;2;2
|
null |
Center for Neural Science, New York University; Flatiron Institute, Simons Foundation; Center for Theoretical Neuroscience, Columbia University; Swartz Program in Theoretical Neuroscience, Kavli Institute for Brain Science, Department of Neuroscience, College of Physicians and Surgeons, Zuckerman Mind Brain Behavior Institute, Columbia University
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6633; None
| null | 0 | null | null | null |
2;3;3;4
| null |
Michelle Miller, SueYeon Chung, Ken Miller
|
https://iclr.cc/virtual/2022/poster/6633
|
divisive normalization;AlexNet;ImageNet;CIFAR-100;manifold capacity;sparsity;receptive fields;Batch Normalization;Group Normalization;Layer Normalization
| null | 2.75 | null |
https://openreview.net/forum?id=aOX3a9q3RVV
|
iclr
| 0.57735 | 0 | null |
main
| 7 |
6;6;8;8
|
3;3;3;3
|
https://iclr.cc/virtual/2022/poster/6633
|
Divisive Feature Normalization Improves Image Recognition Performance in AlexNet
| null | null | 3 | 4.25 |
Poster
|
4;4;4;5
|
2;3;3;3
|
null |
Max Planck Institute for Intelligent Systems, Tübingen, Germany; University of Tübingen, Tübingen, Germany
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6755; None
| null | 0 | null | null | null |
3;3;3
| null |
Maximilian Seitzer, Arash Tavakoli, Dimitrije Antic, Georg Martius
|
https://iclr.cc/virtual/2022/poster/6755
|
Uncertainty Estimation;Probabilistic Neural Networks;Aleatoric Uncertainty;Heteroscedastic Uncertainty;Analysis
| null | 2.666667 | null |
https://openreview.net/forum?id=aPOpXlnV1T
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6
|
4;3;3
|
https://iclr.cc/virtual/2022/poster/6755
|
On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks
| null | null | 3.333333 | 4.333333 |
Poster
|
4;5;4
|
3;2;3
|
null | null |
2022
| 1.5 | null | null | 0 | null | null | null |
1;1;2;2
| null | null | null |
Deep learning;computer vision;semantic segmentation;feature enhancement
| null | 1.5 | null | null |
iclr
| 0 | -0.57735 | null |
main
| 4 |
3;3;5;5
|
3;3;3;1
| null |
Boosting Semantic Segmentation via Feature Enhancement
| null | null | 2.5 | 4.5 |
Withdraw
|
5;4;4;5
|
0;2;2;2
|
null |
Seoul National University
|
2022
| 2.666667 |
https://iclr.cc/virtual/2022/poster/6326; None
| null | 0 | null | null | null |
2;3;3
| null |
Jaewoong Choi, Junho Lee, Changyeon Yoon, Jung Ho Park, Geonho Hwang, Myungjoo Kang
|
https://iclr.cc/virtual/2022/poster/6326
|
generative adversarial network;disentanglement;semantic factorization;latent space control;image manipulation;grassmannian
| null | 2 | null |
https://openreview.net/forum?id=aTzMi4yV_RO
|
iclr
| -0.866025 | -1 | null |
main
| 6.666667 |
6;6;8
|
4;4;3
|
https://iclr.cc/virtual/2022/poster/6326
|
Do Not Escape From the Manifold: Discovering the Local Coordinates on the Latent Space of GANs
| null | null | 3.666667 | 4 |
Poster
|
4;5;3
|
3;3;0
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Autoencoder;sim2real;mpi3d;sviro
| null | 2.25 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5;5
|
3;4;3;3
| null |
Autoencoder for Synthetic to Real Generalization: From Simple to More Complex Scenes
| null | null | 3.25 | 3.75 |
Withdraw
|
4;4;4;3
|
3;2;2;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null | null | null | 3 | null | null |
iclr
| -0.235702 | 0.5 | null |
main
| 6 |
3;5;8;8
|
3;2;4;3
| null |
Specialized Transformers: Faster, Smaller and more Accurate NLP Models
| null | null | 3 | 3.5 |
Reject
|
4;3;4;3
|
3;3;3;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
lottery ticket hypothesis;winning tickets;renormalization group
| null | 2.5 | null | null |
iclr
| 0.132453 | 0.688247 | null |
main
| 4.75 |
3;5;5;6
|
2;2;3;3
| null |
Universality of Deep Neural Network Lottery Tickets: A Renormalization Group Perspective
| null | null | 2.5 | 3.5 |
Reject
|
3;3;5;3
|
1;3;3;3
|
null |
Paper under double-blind review
|
2022
| 1.25 | null | null | 0 | null | null | null |
1;1;1;2
| null | null | null |
causal treatment effect estimation;representation learning;self-supervised learning;end-to-end causal effect estimation;randomized controlled trials
| null | 1.5 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3;3
|
3;2;2;2
| null |
Mimicking Randomized Controlled Trials to Learn End-to-End Patient Representations through Self-Supervised Covariate Balancing for Causal Treatment Effect Estimation
| null | null | 2.25 | 3.5 |
Withdraw
|
3;3;5;3
|
2;2;0;2
|
null |
RIKEN AIP; Hong Kong Baptist University; The University of Melbourne; The University of Sydney; JD Explore Academy, China
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/7212; None
| null | 0 | null | null | null |
2;3;2;3
| null |
Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, Dacheng Tao
|
https://iclr.cc/virtual/2022/poster/7212
|
Positive-Unlabeled Learning;Class-Prior Estimation
| null | 1.75 | null |
https://openreview.net/forum?id=aYAA-XHKyk
|
iclr
| 0.132453 | 0.132453 | null |
main
| 6.25 |
5;6;6;8
|
4;4;2;4
|
https://iclr.cc/virtual/2022/poster/7212
|
Rethinking Class-Prior Estimation for Positive-Unlabeled Learning
| null | null | 3.5 | 3.75 |
Poster
|
4;4;3;4
|
2;3;2;0
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
Reinforcement learning;model-based;multi-agent;deep learning;networked system control.
| null | 1.666667 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5
|
3;4;4
| null |
Fully Decentralized Model-based Policy Optimization with Networked Agents
| null | null | 3.666667 | 3.333333 |
Reject
|
3;4;3
|
2;2;1
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Vertical Federated Learning;Adversarial Attacks;Backdoor Attacks;Feature Recovery;Robustness
| null | 2.25 | null | null |
iclr
| 0 | 0.57735 | null |
main
| 4 |
3;3;5;5
|
2;3;3;3
| null |
RVFR: Robust Vertical Federated Learning via Feature Subspace Recovery
| null | null | 2.75 | 3.5 |
Withdraw
|
4;3;3;4
|
2;2;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
representation learning;statistical learning theory
| null | 2.75 | null | null |
iclr
| -0.438357 | 0.889297 | null |
main
| 5.75 |
3;6;6;8
|
2;3;3;3
| null |
Blessing of Class Diversity in Pre-training
| null | null | 2.75 | 3.5 |
Reject
|
5;3;2;4
|
3;3;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
optimization;graph neural networks;neural reparameterization;neural tangent kernel
| null | 2 | null | null |
iclr
| 0.676481 | 0.676481 | null |
main
| 3.75 |
1;3;5;6
|
3;3;3;4
| null |
Accelerating Optimization using Neural Reparametrization
| null | null | 3.25 | 3.25 |
Reject
|
3;3;3;4
|
1;2;2;3
|
null | null |
2022
| 3.25 | null | null | 0 | null | null | null |
3;4;2;4
| null | null | null |
Private federated learning;fairness
| null | 3 | null | null |
iclr
| -0.96225 | 0.522233 | null |
main
| 4.25 |
3;3;5;6
|
2;3;2;4
| null |
Enforcing fairness in private federated learning via the modified method of differential multipliers
| null | null | 2.75 | 3.5 |
Reject
|
4;4;3;3
|
3;4;2;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null |
Time series forecasting;causal inference;multi-horizon;multi-series forecasting tasks
| null | 1.333333 | null | null |
iclr
| -1 | 0.866025 | null |
main
| 3 |
1;3;5
|
1;3;3
| null |
Causal Triple Attention Time Series Forecasting
| null | null | 2.333333 | 3 |
Withdraw
|
4;3;2
|
0;1;3
|
null | null |
2022
| 1 | null | null | 0 | null | null | null |
1;1;1;1
| null | null | null |
Representation learning;self-supervised learning;video representation learning;pose estimation
| null | 1.75 | null | null |
iclr
| -0.301511 | 0.522233 | null |
main
| 3.5 |
1;3;5;5
|
2;2;2;3
| null |
Self-Supervised Learning of Motion-Informed Latents
| null | null | 2.25 | 4.5 |
Withdraw
|
5;4;5;4
|
1;2;2;2
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
3;2;2
| null | null | null |
Manifold learning;Dimensionality Reduction;Computational Geometry;Simplicial Complex
| null | 1.333333 | null | null |
iclr
| -0.755929 | 0.755929 | null |
main
| 4.666667 |
3;5;6
|
2;2;3
| null |
A Discussion On the Validity of Manifold Learning
| null | null | 2.333333 | 3.666667 |
Withdraw
|
4;4;3
|
2;0;2
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;3;2
| null |
11537
| null |
reinforcement learning;stochastic shortest path
| null | 0.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 5.666667 |
5;6;6
|
4;4;4
| null |
Learning Stochastic Shortest Path with Linear Function Approximation
| null | null | 4 | 3 |
Reject
|
3;3;3
|
0;1;0
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;2;2;3
| null | null | null |
Knowledge Distillation;avoid knowledge leaking
| null | 2.75 | null | null |
iclr
| -0.555556 | 0.19245 | null |
main
| 4.25 |
3;3;5;6
|
4;3;3;4
| null |
Stingy Teacher: Sparse Logits Suffice to Fail Knowledge Distillation
| null | null | 3.5 | 4.25 |
Withdraw
|
5;4;4;4
|
3;2;2;4
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
Differential privacy;feature selection;generalization;high dimension.
| null | 2.5 | null | null |
iclr
| -0.760886 | 0 | null |
main
| 4.75 |
3;5;5;6
|
3;3;3;3
| null |
Larger Model Causes Lower Classification Accuracy Under Differential Privacy: Reason and Solution
| null | null | 3 | 3.25 |
Withdraw
|
4;4;3;2
|
2;2;3;3
|
null |
Google; UC Berkeley
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6295; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Oliver Bryniarski, Nabeel Hingun, Pedro Pachuca, Vincent Wang, Nicholas Carlini
|
https://iclr.cc/virtual/2022/poster/6295
|
Adversarial examples;adversarial attacks
| null | 2.5 | null |
https://openreview.net/forum?id=af1eUDdUVz
|
iclr
| 0.57735 | 0.333333 | null |
main
| 7.5 |
6;8;8;8
|
3;4;3;3
|
https://iclr.cc/virtual/2022/poster/6295
|
Evading Adversarial Example Detection Defenses with Orthogonal Projected Gradient Descent
| null | null | 3.25 | 3.5 |
Poster
|
3;4;4;3
|
2;3;3;2
|
null |
NVIDIA & Caltech; NVIDIA; Northeastern University; NVIDIA & ASU; NVIDIA & UT Austin; UCLA
|
2022
| 2.333333 |
https://iclr.cc/virtual/2022/poster/6087; None
| null | 0 | null | null | null |
2;2;3
| null |
Xiaojian Ma, Weili Nie, Zhiding Yu, Huaizu Jiang, Chaowei Xiao, Yuke Zhu, Song-Chun Zhu, Anima Anandkumar
|
https://iclr.cc/virtual/2022/poster/6087
|
visual relational reasoning;representation learning;systematic generalization
| null | 2.666667 | null |
https://openreview.net/forum?id=afoV8W3-IYp
|
iclr
| 0.5 | 0 | null |
main
| 6.666667 |
6;6;8
|
3;3;3
|
https://iclr.cc/virtual/2022/poster/6087
|
RelViT: Concept-guided Vision Transformer for Visual Relational Reasoning
| null | null | 3 | 3.333333 |
Poster
|
4;2;4
|
3;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null | null | null | 2.5 | null | null |
iclr
| 0.707107 | 1 | null |
main
| 6.5 |
5;5;8;8
|
3;3;4;4
| null |
DFSSATTEN: Dynamic Fine-grained Structured Sparse Attention Mechanism
| null | null | 3.5 | 4 |
Reject
|
4;3;5;4
|
2;2;3;3
|
null |
State Key Lab of CAD&CG, Zhejiang University; FABU Inc.; State Key Lab of CAD&CG, Zhejiang University; FABU Inc.
|
2022
| 2.8 |
https://iclr.cc/virtual/2022/poster/5913; None
| null | 0 | null | null | null |
2;3;3;3;3
| null |
Liang Peng, Senbo Yan, Boxi Wu, Zheng Yang, Xiaofei He, Deng Cai
|
https://iclr.cc/virtual/2022/poster/5913
|
Computer vision;monocular 3D object detection;weakly supervised
| null | 2.6 | null |
https://openreview.net/forum?id=ahi2XSHpAUZ
|
iclr
| -0.25 | -0.25 | null |
main
| 6.4 |
6;6;6;6;8
|
4;3;3;3;3
|
https://iclr.cc/virtual/2022/poster/5913
|
WeakM3D: Towards Weakly Supervised Monocular 3D Object Detection
|
https://github.com/SPengLiang/WeakM3D
| null | 3.2 | 4.2 |
Poster
|
4;5;4;4;4
|
3;3;2;2;3
|
null |
Google Cloud AI; Google Research, Brain Team
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6655; None
| null | 0 | null | null | null |
3;2;3;3
| null |
Hanjun Dai, Yuan Xue, Zia Syed, Dale Schuurmans, Bo Dai
|
https://iclr.cc/virtual/2022/poster/6655
|
data-driven algorithm design;learning to optimize;multi-stage stochastic optimization;primal-dual dynamic programming
| null | 2.75 | null |
https://openreview.net/forum?id=aisKPsMM3fg
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
3;4;4;3
|
https://iclr.cc/virtual/2022/poster/6655
|
Neural Stochastic Dual Dynamic Programming
| null | null | 3.5 | 3.5 |
Poster
|
4;3;2;5
|
2;3;3;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;2;3
| null | null | null |
transfer learning;compositional generalization
| null | 2.666667 | null | null |
iclr
| 0 | 0.5 | null |
main
| 5.666667 |
5;6;6
|
3;4;3
| null |
Learning to Generalize Compositionally by Transferring Across Semantic Parsing Tasks
| null | null | 3.333333 | 4 |
Reject
|
4;4;4
|
2;3;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;3;3
| null | null | null |
Antimicrobial Peptides;Drug Discovery;Secondary Structure;VQ-VAE
| null | 1.666667 | null | null |
iclr
| 0 | 0.981981 | null |
main
| 4 |
1;5;6
|
2;3;3
| null |
Generating Antimicrobial Peptides from Latent Secondary Structure Space
| null | null | 2.666667 | 4 |
Reject
|
4;4;4
|
1;2;2
|
null |
Stanford University; Rutgers University
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/7140; None
| null | 0 | null | null | null |
3;3;3;3;3
| null |
Huaxiu Yao, Linjun Zhang, Chelsea Finn
|
https://iclr.cc/virtual/2022/poster/7140
|
meta-learning;task interpolation;meta-regularization
| null | 2.8 | null |
https://openreview.net/forum?id=ajXWF7bVR8d
|
iclr
| 0 | 0 | null |
main
| 8 |
8;8;8;8;8
|
3;4;3;3;4
|
https://iclr.cc/virtual/2022/poster/7140
|
Meta-Learning with Fewer Tasks through Task Interpolation
| null | null | 3.4 | 3.4 |
Oral
|
3;4;3;4;3
|
3;3;3;3;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
contrastive learning;supervised contrastive learning;transfer learning;robustness;noisy labels;coresets
| null | 2 | null | null |
iclr
| -0.707107 | 0.707107 | null |
main
| 4 |
3;3;5;5
|
2;3;4;3
| null |
The Details Matter: Preventing Class Collapse in Supervised Contrastive Learning
| null | null | 3 | 3 |
Withdraw
|
4;3;2;3
|
2;2;2;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Stochastic Line Search;Stochastic Model Building;Non-convex Stochastic Optimization;Unconstrained Optimization
| null | 1.25 | null | null |
iclr
| 0.816497 | 0.333333 | null |
main
| 4.5 |
3;5;5;5
|
3;3;4;3
| null |
Bolstering Stochastic Gradient Descent with Model Building
| null | null | 3.25 | 4 |
Reject
|
3;4;4;5
|
1;2;0;2
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null | null | null | 2.333333 | null | null |
iclr
| 0.866025 | 0.5 | null |
main
| 3.666667 |
3;3;5
|
3;2;3
| null |
Modeling Adversarial Noise for Adversarial Defense
| null | null | 2.666667 | 4 |
Reject
|
4;3;5
|
3;2;2
|
null | null |
2022
| 1.666667 | null | null | 0 | null | null | null |
1;1;3
| null | null | null |
RKBS;RKHS;concatenated kernel learning;representation learning;deep learning;MLMKL;Deep Gaussian Processes;gaussian processes;kernel machines
| null | 1.333333 | null | null |
iclr
| -0.866025 | 1 | null |
main
| 2.333333 |
1;3;3
|
2;4;4
| null |
Deep banach space kernels
| null | null | 3.333333 | 4 |
Reject
|
5;3;4
|
1;1;2
|
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