Papers
Learning Determinantal Point Processes with Moments and Cycles
John Urschel, Victor-Emmanuel Brunel, Ankur Moitra et al.
Learning Stable Stochastic Nonlinear Dynamical Systems
Jonas Umlauft, Sandra Hirche
Multilabel Classification with Group Testing and Codes
Shashanka Ubaru, Arya Mazumdar
Breaking Locality Accelerates Block Gauss-Seidel
Stephen Tu, Shivaram Venkataraman, Ashia C. Wilson et al.
Hyperplane Clustering via Dual Principal Component Pursuit
Manolis C. Tsakiris, René Vidal
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
Rakshit Trivedi, Hanjun Dai, Yichen Wang et al.
Magnetic Hamiltonian Monte Carlo
Nilesh Tripuraneni, Mark Rowland, Zoubin Ghahramani et al.
Diameter-Based Active Learning
Christopher Tosh, Sanjoy Dasgupta
Boosted Fitted Q-Iteration
Samuele Tosatto, Matteo Pirotta, Carlo D’Eramo et al.
Accelerating Eulerian Fluid Simulation With Convolutional Networks
Jonathan Tompson, Kristofer Schlachter, Pablo Sprechmann et al.
Evaluating the Variance of Likelihood-Ratio Gradient Estimators
Seiya Tokui, Issei Sato
Stochastic DCA for the Large-sum of Non-convex Functions Problem and its Application to Group Variable Selection in Classification
Hoai An Le Thi, Hoai Minh Le, Duy Nhat Phan et al.
Neural Networks and Rational Functions
Matus Telgarsky
Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares
Junqi Tang, Mohammad Golbabaee, Mike E. Davies
Gradient Coding: Avoiding Stragglers in Distributed Learning
Rashish Tandon, Qi Lei, Alexandros G. Dimakis et al.
Partitioned Tensor Factorizations for Learning Mixed Membership Models
Zilong Tan, Sayan Mukherjee
Coherent Probabilistic Forecasts for Hierarchical Time Series
Souhaib Ben Taieb, James W. Taylor, Rob J. Hyndman
Selective Inference for Sparse High-Order Interaction Models
Shinya Suzumura, Kazuya Nakagawa, Yuta Umezu et al.
Distributed Mean Estimation with Limited Communication
Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar et al.
Axiomatic Attribution for Deep Networks
Mukund Sundararajan, Ankur Taly, Qiqi Yan
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction
Wen Sun, Arun Venkatraman, Geoffrey J. Gordon et al.
meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting
Xu Sun, Xuancheng Ren, Shuming Ma et al.
Relative Fisher Information and Natural Gradient for Learning Large Modular Models
Ke Sun, Frank Nielsen
Safety-Aware Algorithms for Adversarial Contextual Bandit
Wen Sun, Debadeepta Dey, Ashish Kapoor