Papers
On the Expressive Power of Deep Polynomial Neural Networks
Joe Kileel, Matthew Trager, Joan Bruna
Selective Sampling-based Scalable Sparse Subspace Clustering
Shin Matsushima, Maria Brbic
Online Stochastic Shortest Path with Bandit Feedback and Unknown Transition Function
Aviv Rosenberg, Yishay Mansour
Network Pruning via Transformable Architecture Search
Xuanyi Dong, Yi Yang
Aligning Visual Regions and Textual Concepts for Semantic-Grounded Image Representations
Fenglin Liu, Yuanxin Liu, Xuancheng Ren et al.
Finite-Sample Analysis for SARSA with Linear Function Approximation
Shaofeng Zou, Tengyu Xu, Yingbin Liang
Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm
Giulia Luise, Saverio Salzo, Massimiliano Pontil et al.
Reconciling λ-Returns with Experience Replay
Brett Daley, Christopher Amato
Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization
Gautam Goel, Yiheng Lin, Haoyuan Sun et al.
Re-randomized Densification for One Permutation Hashing and Bin-wise Consistent Weighted Sampling
Ping Li, Xiaoyun Li, Cun-Hui Zhang
The Normalization Method for Alleviating Pathological Sharpness in Wide Neural Networks
Ryo Karakida, Shotaro Akaho, Shun-ichi Amari
An Embedding Framework for Consistent Polyhedral Surrogates
Jessica Finocchiaro, Rafael Frongillo, Bo Waggoner
Generative Well-intentioned Networks
Justin Cosentino, Jun Zhu
Integer Discrete Flows and Lossless Compression
Emiel Hoogeboom, Jorn Peters, Rianne van den Berg et al.
Regret Minimization for Reinforcement Learning by Evaluating the Optimal Bias Function
Zihan Zhang, Xiangyang Ji
Policy Learning for Fairness in Ranking
Ashudeep Singh, Thorsten Joachims
AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification
Ronghui You, Zihan Zhang, Ziye Wang et al.
Computing Full Conformal Prediction Set with Approximate Homotopy
Eugene Ndiaye, Ichiro Takeuchi
Large Memory Layers with Product Keys
Guillaume Lample, Alexandre Sablayrolles, Marc'Aurelio Ranzato et al.
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics
Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel et al.
Graph Transformer Networks
Seongjun Yun, Minbyul Jeong, Raehyun Kim et al.
Partially Encrypted Deep Learning using Functional Encryption
Théo Ryffel, David Pointcheval, Francis Bach et al.
A Zero-Positive Learning Approach for Diagnosing Software Performance Regressions
Mejbah Alam, Justin Gottschlich, Nesime Tatbul et al.
Differentiable Convex Optimization Layers
Akshay Agrawal, Brandon Amos, Shane Barratt et al.