Papers
Kernel Based Progressive Distillation for Adder Neural Networks
Yixing Xu, Chang Xu, Xinghao Chen et al.
Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax
Andres Potapczynski, Gabriel Loaiza-Ganem, John P. Cunningham
Locally Differentially Private (Contextual) Bandits Learning
Kai Zheng, Tianle Cai, Weiran Huang et al.
Learning Black-Box Attackers with Transferable Priors and Query Feedback
Jiancheng YANG, Yangzhou Jiang, Xiaoyang Huang et al.
Your GAN is Secretly an Energy-based Model and You Should Use Discriminator Driven Latent Sampling
Tong Che, Ruixiang ZHANG, Jascha Sohl-Dickstein et al.
Causal Imitation Learning With Unobserved Confounders
Junzhe Zhang, Daniel Kumor, Elias Bareinboim
Minimax Estimation of Conditional Moment Models
Nishanth Dikkala, Greg Lewis, Lester W. Mackey et al.
Few-Cost Salient Object Detection with Adversarial-Paced Learning
Dingwen Zhang, HaiBin Tian, Jungong Han
Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method
Kiran K Thekumparampil, Prateek Jain, Praneeth Netrapalli et al.
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization
Benjamin Aubin, Florent Krzakala, Yue Lu et al.
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses
Kaivalya Rawal, Himabindu Lakkaraju
How Robust are the Estimated Effects of Nonpharmaceutical Interventions against COVID-19?
Mrinank Sharma, Sören Mindermann, Jan Brauner et al.
Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning
Nino Vieillard, Tadashi Kozuno, Bruno Scherrer et al.
Safe Reinforcement Learning via Curriculum Induction
Matteo Turchetta, Andrey Kolobov, Shital Shah et al.
Improving Neural Network Training in Low Dimensional Random Bases
Frithjof Gressmann, Zach Eaton-Rosen, Carlo Luschi
FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training
Yonggan Fu, Haoran You, Yang Zhao et al.
Deeply Learned Spectral Total Variation Decomposition
Tamara G. Grossmann, Yury Korolev, Guy Gilboa et al.
Training Generative Adversarial Networks with Limited Data
Tero Karras, Miika Aittala, Janne Hellsten et al.
Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation
Devavrat Shah, Dogyoon Song, Zhi Xu et al.
MetaPoison: Practical General-purpose Clean-label Data Poisoning
W. Ronny Huang, Jonas Geiping, Liam Fowl et al.
A Bandit Learning Algorithm and Applications to Auction Design
Kim Thang Nguyen
Neural Architecture Generator Optimization
Robin Ru, Pedro Esperança, Fabio Maria Carlucci
Neural Topographic Factor Analysis for fMRI Data
Eli Sennesh, Zulqarnain Khan, Yiyu Wang et al.
TSPNet: Hierarchical Feature Learning via Temporal Semantic Pyramid for Sign Language Translation
DONGXU LI, Chenchen Xu, Xin Yu et al.