Papers
Exact expressions for double descent and implicit regularization via surrogate random design
Michal Derezinski, Feynman T Liang, Michael W. Mahoney
Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks
Umut Simsekli, Ozan Sener, George Deligiannidis et al.
Model Inversion Networks for Model-Based Optimization
Aviral Kumar, Sergey Levine
Causal Estimation with Functional Confounders
Aahlad Puli, Adler J. Perotte, Rajesh Ranganath
Feature Importance Ranking for Deep Learning
Maksymilian Wojtas, Ke Chen
Attribution Preservation in Network Compression for Reliable Network Interpretation
Geondo Park, June Yong Yang, Sung Ju Hwang et al.
Decision-Making with Auto-Encoding Variational Bayes
Romain Lopez, Pierre Boyeau, Nir Yosef et al.
A new inference approach for training shallow and deep generalized linear models of noisy interacting neurons
Gabriel Mahuas, Giulio Isacchini, Olivier Marre et al.
Neural Dynamic Policies for End-to-End Sensorimotor Learning
Shikhar Bahl, Mustafa Mukadam, Abhinav Gupta et al.
Meta-Neighborhoods
Siyuan Shan, Yang Li, Junier B Oliva
Deep Direct Likelihood Knockoffs
Mukund Sudarshan, Wesley Tansey, Rajesh Ranganath
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Meng Liu, David F Gleich
HOI Analysis: Integrating and Decomposing Human-Object Interaction
Yong-Lu Li, Xinpeng Liu, Xiaoqian Wu et al.
Continual Learning of Control Primitives : Skill Discovery via Reset-Games
Kelvin Xu, Siddharth Verma, Chelsea Finn et al.
Certifying Strategyproof Auction Networks
Michael Curry, Ping-yeh Chiang, Tom Goldstein et al.
Network size and size of the weights in memorization with two-layers neural networks
Sebastien Bubeck, Ronen Eldan, Yin Tat Lee et al.
Domain Adaptation as a Problem of Inference on Graphical Models
Kun Zhang, Mingming Gong, Petar Stojanov et al.
Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nystrom method
Michal Derezinski, Rajiv Khanna, Michael W. Mahoney
Learning Differentiable Programs with Admissible Neural Heuristics
Ameesh Shah, Eric Zhan, Jennifer Sun et al.
Stochastic Optimization for Performative Prediction
Celestine Mendler-Dünner, Juan Perdomo, Tijana Zrnic et al.
Towards Deeper Graph Neural Networks with Differentiable Group Normalization
Kaixiong Zhou, Xiao Huang, Yuening Li et al.
Telescoping Density-Ratio Estimation
Benjamin Rhodes, Kai Xu, Michael U. Gutmann
Minimax Dynamics of Optimally Balanced Spiking Networks of Excitatory and Inhibitory Neurons
Qianyi Li, Cengiz Pehlevan
Probabilistic Orientation Estimation with Matrix Fisher Distributions
David Mohlin, Josephine Sullivan, Gérald Bianchi
Delay and Cooperation in Nonstochastic Linear Bandits
Shinji Ito, Daisuke Hatano, Hanna Sumita et al.