Papers
Multirate Training of Neural Networks
Tiffany J Vlaar, Benedict Leimkuhler
Multi Resolution Analysis (MRA) for Approximate Self-Attention
Zhanpeng Zeng, Sourav Pal, Jeffery Kline et al.
Multi-scale Feature Learning Dynamics: Insights for Double Descent
Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio et al.
Multi-slots Online Matching with High Entropy
Xingyu Lu, Qintong Wu, Wenliang Zhong
Multi-Task Learning as a Bargaining Game
Aviv Navon, Aviv Shamsian, Idan Achituve et al.
NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning
Wentao Zhang, Zeang Sheng, Mingyu Yang et al.
Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning
Martin Genzel, Ingo Gühring, Jan Macdonald et al.
Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation
Pihe Hu, Yu Chen, Longbo Huang
Nearly Optimal Catoni’s M-estimator for Infinite Variance
Sujay Bhatt, Guanhua Fang, Ping Li et al.
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee
Tianhao Wu, Yunchang Yang, Han Zhong et al.
Near-Optimal Algorithms for Autonomous Exploration and Multi-Goal Stochastic Shortest Path
Haoyuan Cai, Tengyu Ma, Simon Du
Near-Optimal Learning of Extensive-Form Games with Imperfect Information
Yu Bai, Chi Jin, Song Mei et al.
Near-optimal rate of consistency for linear models with missing values
Alexis Ayme, Claire Boyer, Aymeric Dieuleveut et al.
Nested Bandits
Matthieu Martin, Panayotis Mertikopoulos, Thibaud Rahier et al.
Nesterov Accelerated Shuffling Gradient Method for Convex Optimization
Trang H Tran, Katya Scheinberg, Lam M Nguyen
NeuralEF: Deconstructing Kernels by Deep Neural Networks
Zhijie Deng, Jiaxin Shi, Jun Zhu
Neural Fisher Discriminant Analysis: Optimal Neural Network Embeddings in Polynomial Time
Burak Bartan, Mert Pilanci
Neural Implicit Dictionary Learning via Mixture-of-Expert Training
Peihao Wang, Zhiwen Fan, Tianlong Chen et al.
Neural Inverse Kinematic
Raphael Bensadoun, Shir Gur, Nitsan Blau et al.
Neural Inverse Transform Sampler
Henry Li, Yuval Kluger
Neural Language Models are not Born Equal to Fit Brain Data, but Training Helps
Alexandre Pasquiou, Yair Lakretz, John T Hale et al.
Neural Laplace: Learning diverse classes of differential equations in the Laplace domain
Samuel I Holt, Zhaozhi Qian, Mihaela van der Schaar
Neural Network Poisson Models for Behavioural and Neural Spike Train Data
Moein Khajehnejad, Forough Habibollahi, Richard Nock et al.
Neural Network Pruning Denoises the Features and Makes Local Connectivity Emerge in Visual Tasks
Franco Pellegrini, Giulio Biroli
Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective
Jingzhao Zhang, Haochuan Li, Suvrit Sra et al.