ICLR

MonoDistill: Learning Spatial Features for Monocular 3D Object Detection

Zhiyu Chong, Xinzhu Ma, Hong Zhang, Yuxin Yue, Haojie Li, Zhihui Wang, Wanli Ouyang

Comments Accepted by ICLR 2022

What's Wrong with Deep Learning in Tree Search for Combinatorial Optimization

Maximilian Böther, Otto Kißig, Martin Taraz, Sarel Cohen, Karen Seidel, Tobias Friedrich

Comments 25 pages, accepted for publication at ICLR 2022

Contrastive Representation Distillation

Yonglong Tian, Dilip Krishnan, Phillip Isola

Comments ICLR 2020. Project Page: http://hobbitlong.github.io/CRD/, Code: http://github.com/HobbitLong/RepDistiller. Typo fixed in the newest version

Hot-Refresh Model Upgrades with Regression-Alleviating Compatible Training in Image Retrieval

Binjie Zhang, Yixiao Ge, Yantao Shen, Yu Li, Chun Yuan, Xuyuan Xu, Yexin Wang, Ying Shan

Comments Accepted to ICLR 2022

Learning to Complete Code with Sketches

Daya Guo, Alexey Svyatkovskiy, Jian Yin, Nan Duan, Marc Brockschmidt, Miltiadis Allamanis

Comments Published in ICLR 2022

Concurrent Adversarial Learning for Large-Batch Training

Yong Liu, Xiangning Chen, Minhao Cheng, Cho-Jui Hsieh, Yang You

Comments Accepted to ICLR 2022

Scattering Networks on the Sphere for Scalable and Rotationally Equivariant Spherical CNNs

Jason D. McEwen, Christopher G. R. Wallis, Augustine N. Mavor-Parker

Comments 18 pages, 6 figures, accepted by ICLR, code at https://www.kagenova.com/products/fourpiAI/

GreaseLM: Graph REASoning Enhanced Language Models for Question Answering

Xikun Zhang, Antoine Bosselut, Michihiro Yasunaga, Hongyu Ren, Percy Liang, Christopher D. Manning, Jure Leskovec

Comments Published at ICLR 2022. All code, data, and pretrained models are available at https://github.com/snap-stanford/GreaseLM

Task Affinity with Maximum Bipartite Matching in Few-Shot Learning

Cat P. Le, Juncheng Dong, Mohammadreza Soltani, Vahid Tarokh

Comments Accepted as a conference paper at ICLR 2022

Fast Differentiable Matrix Square Root

Yue Song, Nicu Sebe, Wei Wang

Comments Accpeted by ICLR 2022

MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining

Ahmed Imtiaz Humayun, Randall Balestriero, Richard Baraniuk

Comments ICLR Accepted version, 28 pages, 23 figures

A generalization of the randomized singular value decomposition

Nicolas Boullé, Alex Townsend

Comments Accepted at ICLR 2022

Attacking Neural Text Detectors

Max Wolff, Stuart Wolff

Comments Accepted at the ICLR 2020 workshop "Towards Trustworthy ML: Rethinking Security and Privacy for ML."

Fair Interpretable Learning via Correction Vectors

Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer

Comments ICLR-21 Workshop on Responsible AI

Fair Group-Shared Representations with Normalizing Flows

Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer

Comments ICLR-21 Workshop on Responsible AI

Robust Subspace Recovery Layer for Unsupervised Anomaly Detection

Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman

Comments This work is on the ICLR 2020 conference

Journal ref Eighth International Conference on Learning Representations (ICLR), 2020, https://openreview.net/pdf?id=rylb3eBtwr

Implicit Bias of MSE Gradient Optimization in Underparameterized Neural Networks

Benjamin Bowman, Guido Montufar

Comments 61 pages, submitted to ICLR 2022

Entropic gradient descent algorithms and wide flat minima

Fabrizio Pittorino, Carlo Lucibello, Christoph Feinauer, Gabriele Perugini, Carlo Baldassi, Elizaveta Demyanenko, Riccardo Zecchina

Comments ICLR 2021 camera-ready

Acoustic Neighbor Embeddings

Woojay Jeon

Comments Anonymized version submitted to ICLR 2021

Training and Generating Neural Networks in Compressed Weight Space

Kazuki Irie, Jürgen Schmidhuber

Comments Presented at ICLR 2021 Workshop on Neural Compression, https://openreview.net/forum?id=qU1EUxdVd_D

Network Group Testing

Paolo Bertolotti, Ali Jadbabaie

Comments Updated to version presented at ICLR 2021 AI for Public Health Workshop

Neural Thompson Sampling

Weitong Zhang, Dongruo Zhou, Lihong Li, Quanquan Gu

Comments 26 pages, 2 tables, 5 figures. In ICLR 2021

How Much Over-parameterization Is Sufficient to Learn Deep ReLU Networks?

Zixiang Chen, Yuan Cao, Difan Zou, Quanquan Gu

Comments 21 pages, 1 figure, 1 table. In ICLR 2021

Online Adversarial Purification based on Self-Supervision

Changhao Shi, Chester Holtz, Gal Mishne

Comments Accepted to ICLR 2021

Is Attention Better Than Matrix Decomposition?

Zhengyang Geng, Meng-Hao Guo, Hongxu Chen, Xia Li, Ke Wei, Zhouchen Lin

Comments ICLR 2021

Calibration of Neural Networks using Splines

Kartik Gupta, Amir Rahimi, Thalaiyasingam Ajanthan, Thomas Mensink, Cristian Sminchisescu, Richard Hartley

Comments ICLR 2021

Shapley explainability on the data manifold

Christopher Frye, Damien de Mijolla, Tom Begley, Laurence Cowton, Megan Stanley, Ilya Feige

Comments To appear in ICLR 2021; 9 pages, 6 figures, 2 appendices

HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients

Enmao Diao, Jie Ding, Vahid Tarokh

Comments ICLR 2021

Latent Space Oddity: on the Curvature of Deep Generative Models

Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg

Comments Published at International Conference on Learning Representations (ICLR) 2018

Detecting Underspecification with Local Ensembles

David Madras, James Atwood, Alex D'Amour

Comments Published as a conference paper at ICLR 2020 under the title "Detecting Extrapolation with Local Ensembles"