Papers
Mutual Information Regularized Offline Reinforcement Learning
Xiao Ma, Bingyi Kang, Zhongwen Xu et al.
MVDiffusion: Enabling Holistic Multi-view Image Generation with Correspondence-Aware Diffusion
Shitao Tang, Fuyang Zhang, Jiacheng Chen et al.
MVDoppler: Unleashing the Power of Multi-View Doppler for MicroMotion-based Gait Classification
Soheil Hor, Shubo Yang, Jaeho Choi et al.
NAP: Neural 3D Articulated Object Prior
Jiahui Lei, Congyue Deng, William B Shen et al.
NAR-Former V2: Rethinking Transformer for Universal Neural Network Representation Learning
Yun Yi, Haokui Zhang, Rong Xiao et al.
Nash Regret Guarantees for Linear Bandits
Ayush Sawarni, Soumyabrata Pal, Siddharth Barman
NAS-X: Neural Adaptive Smoothing via Twisting
Dieterich Lawson, Michael Li, Scott Linderman
Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation
Ruida Zhou, Tao Liu, Min Cheng et al.
Natural Language Instruction-following with Task-related Language Development and Translation
Jing-Cheng Pang, Xin-Yu Yang, Si-Hang Yang et al.
NAVI: Category-Agnostic Image Collections with High-Quality 3D Shape and Pose Annotations
Varun Jampani, Kevis-kokitsi Maninis, Andreas Engelhardt et al.
Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Federated Object Detection
Taehyeon Kim, Eric Lin, Junu Lee et al.
Navigating the Pitfalls of Active Learning Evaluation: A Systematic Framework for Meaningful Performance Assessment
Carsten Lüth, Till Bungert, Lukas Klein et al.
NCDL: A Framework for Deep Learning on non-Cartesian Lattices
Joshua Horacsek, Usman Alim
Nearest Neighbour with Bandit Feedback
Stephen Pasteris, Chris Hicks, Vasilios Mavroudis
Near-Linear Time Algorithm for the Chamfer Distance
Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram et al.
Nearly Optimal Bounds for Cyclic Forgetting
William Swartworth, Deanna Needell, Rachel Ward et al.
Nearly Optimal VC-Dimension and Pseudo-Dimension Bounds for Deep Neural Network Derivatives
Yahong Yang, Haizhao Yang, Yang Xiang
Nearly Tight Bounds For Differentially Private Multiway Cut
Mina Dalirrooyfard, Slobodan Mitrovic, Yuriy Nevmyvaka
Near-Optimal $k$-Clustering in the Sliding Window Model
David Woodruff, Peilin Zhong, Samson Zhou
Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression
Ilias Diakonikolas, Daniel Kane, Ankit Pensia et al.
Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise
Ilias Diakonikolas, Jelena Diakonikolas, Daniel Kane et al.
Near-optimal learning with average Hölder smoothness
Guy Kornowski, Steve Hanneke, Aryeh Kontorovich
Near Optimal Reconstruction of Spherical Harmonic Expansions
Amir Zandieh, Insu Han, Haim Avron
Necessary and Sufficient Conditions for Optimal Decision Trees using Dynamic Programming
Jacobus van der Linden, Mathijs de Weerdt, Emir Demirović
NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks
Seokil Ham, Jungwuk Park, Dong-Jun Han et al.