Papers
Multi-Objective Non-parametric Sequential Prediction
Guy Uziel, Ran El-Yaniv
Multi-output Polynomial Networks and Factorization Machines
Mathieu Blondel, Vlad Niculae, Takuma Otsuka et al.
Multiplicative Weights Update with Constant Step-Size in Congestion Games: Convergence, Limit Cycles and Chaos
Gerasimos Palaiopanos, Ioannis Panageas, Georgios Piliouras
Multiresolution Kernel Approximation for Gaussian Process Regression
Yi Ding, Risi Kondor, Jonathan Eskreis-Winkler
Multiscale Quantization for Fast Similarity Search
Xiang Wu, Ruiqi Guo, Ananda Theertha Suresh et al.
Multiscale Semi-Markov Dynamics for Intracortical Brain-Computer Interfaces
Daniel Milstein, Jason Pacheco, Leigh Hochberg et al.
Multi-Task Learning for Contextual Bandits
Aniket Anand Deshmukh, Urun Dogan, Clay Scott
Multitask Spectral Learning of Weighted Automata
Guillaume Rabusseau, Borja Balle, Joelle Pineau
Multi-View Decision Processes: The Helper-AI Problem
Christos Dimitrakakis, David C. Parkes, Goran Radanovic et al.
Multi-view Matrix Factorization for Linear Dynamical System Estimation
Mahdi Karami, Martha White, Dale Schuurmans et al.
Multi-way Interacting Regression via Factorization Machines
Mikhail Yurochkin, Xuanlong Nguyen, nikolaos Vasiloglou
Natural Value Approximators: Learning when to Trust Past Estimates
Zhongwen Xu, Joseph Modayil, Hado P van Hasselt et al.
Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions
Aryeh Kontorovich, Sivan Sabato, Roi Weiss
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
Jason Altschuler, Jonathan Niles-Weed, Philippe Rigollet
Near Minimax Optimal Players for the Finite-Time 3-Expert Prediction Problem
Yasin Abbasi Yadkori, Peter L Bartlett, Victor Gabillon
Near-Optimal Edge Evaluation in Explicit Generalized Binomial Graphs
Sanjiban Choudhury, Shervin Javdani, Siddhartha Srinivasa et al.
Near Optimal Sketching of Low-Rank Tensor Regression
Xingguo Li, Jarvis Haupt, David Woodruff
Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee
Alireza Aghasi, Afshin Abdi, Nam Nguyen et al.
Neural Discrete Representation Learning
Aaron van den Oord, Oriol Vinyals, koray kavukcuoglu
Neural Expectation Maximization
Klaus Greff, Sjoerd van Steenkiste, Jürgen Schmidhuber
NeuralFDR: Learning Discovery Thresholds from Hypothesis Features
Fei Xia, Martin J Zhang, James Y Zou et al.
Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons
Nikhil Parthasarathy, Eleanor Batty, William Falcon et al.
Neural Program Meta-Induction
Jacob Devlin, Rudy R Bunel, Rishabh Singh et al.
Neural system identification for large populations separating “what” and “where”
David Klindt, Alexander S Ecker, Thomas Euler et al.
Neural Variational Inference and Learning in Undirected Graphical Models
Volodymyr Kuleshov, Stefano Ermon