ICML Papers
5,975 papers found • Page 40 of 120
Nesterov Method for Asynchronous Pipeline Parallel Optimization
Thalaiyasingam Ajanthan, Sameera Ramasinghe, Yan Zuo et al.
NestQuant: nested lattice quantization for matrix products and LLMs
Semyon Savkin, Eitan Porat, Or Ordentlich et al.
NETS: A Non-equilibrium Transport Sampler
Michael Albergo, Eric Vanden-Eijnden
Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning
Guozheng Ma, Lu Li, Zilin Wang et al.
NeuralCohort: Cohort-aware Neural Representation Learning for Healthcare Analytics
Changshuo Liu, Lingze Zeng, Kaiping Zheng et al.
Neural Collapse Beyond the Unconstrained Features Model: Landscape, Dynamics, and Generalization in the Mean-Field Regime
Diyuan Wu, Marco Mondelli
Neural Discovery in Mathematics: Do Machines Dream of Colored Planes?
Konrad Mundinger, Max Zimmer, Aldo Kiem et al.
Neural Encoding and Decoding at Scale
Yizi Zhang, Yanchen Wang, Mehdi Azabou et al.
Neural Event-Triggered Control with Optimal Scheduling
Luan Yang, Jingdong Zhang, Qunxi Zhu et al.
Neural Genetic Search in Discrete Spaces
Hyeonah Kim, Sanghyeok Choi, Jiwoo Son et al.
Neural Graph Matching Improves Retrieval Augmented Generation in Molecular Machine Learning
Runzhong Wang, Rui-Xi Wang, Mrunali Manjrekar et al.
Neural Guided Diffusion Bridges
Gefan Yang, Frank van der Meulen, Stefan Sommer
Neural Interpretable PDEs: Harmonizing Fourier Insights with Attention for Scalable and Interpretable Physics Discovery
Ning Liu, Yue Yu
Neural Representational Consistency Emerges from Probabilistic Neural-Behavioral Representation Alignment
Yu Zhu, Chunfeng Song, Wanli Ouyang et al.
Neural Solver Selection for Combinatorial Optimization
Chengrui Gao, Haopu Shang, Ke Xue et al.
NeuronTune: Towards Self-Guided Spurious Bias Mitigation
Guangtao Zheng, Wenqian Ye, Aidong Zhang
Neurosymbolic World Models for Sequential Decision Making
Leonardo Hernandez Cano, Maxine Perroni-Scharf, Neil Dhir et al.
NeuroTree: Hierarchical Functional Brain Pathway Decoding for Mental Health Disorders
Jun-En Ding, Dongsheng Luo, Chenwei Wu et al.
Neutral residues: revisiting adapters for model extension
Franck TALLA, Edouard Grave, Herve Jegou
New Bounds for Sparse Variational Gaussian Processes
Michalis Titsias
NextCoder: Robust Adaptation of Code LMs to Diverse Code Edits
Tushar Aggarwal, Swayam Singh, Abhijeet Awasthi et al.
NExtLong: Toward Effective Long-Context Training without Long Documents
Chaochen Gao, Xing W, Zijia Lin et al.
NICE Data Selection for Instruction Tuning in LLMs with Non-differentiable Evaluation Metric
Jingtan Wang, Xiaoqiang Lin, Rui Qiao et al.
NMA-tune: Generating Highly Designable and Dynamics Aware Protein Backbones
Urszula Julia Komorowska, Francisco Vargas, Alessandro Rondina et al.
No Free Lunch from Random Feature Ensembles: Scaling Laws and Near-Optimality Conditions
Benjamin Ruben, William Tong, Hamza Chaudhry et al.
Noise Conditional Variational Score Distillation
Xinyu Peng, Ziyang Zheng, Yaoming Wang et al.
Noise-Guided Predicate Representation Extraction and Diffusion-Enhanced Discretization for Scene Graph Generation
Guoqing Zhang, Shichao Kan, Fanghui Zhang et al.
Noisy SIGNSGD Is More Differentially Private Than You (Might) Think
Richeng Jin, Huaiyu (David) Dai
NoLiMa: Long-Context Evaluation Beyond Literal Matching
Ali Modarressi, Hanieh Deilamsalehy, Franck Dernoncourt et al.
No Metric to Rule Them All: Toward Principled Evaluations of Graph-Learning Datasets
Corinna Coupette, Jeremy Wayland, Emily Simons et al.
Non-Asymptotic and Non-Lipschitzian Bounds on Optimal Values in Stochastic Optimization Under Heavy Tails
Jindong Tong, Hongcheng Liu, Johannes Royset
Non-asymptotic Error Bounds in $\mathcal{W}_2$-Distance with Sqrt(d) Dimension Dependence and First Order Convergence for Langevin Monte Carlo beyond Log-Concavity
Bin Yang, Xiaojie Wang
Non-Asymptotic Length Generalization
Thomas Chen, Tengyu Ma, Zhiyuan Li
Nonconvex Theory of $M$-estimators with Decomposable Regularizers
Weiwei Liu
Nonlinearly Preconditioned Gradient Methods under Generalized Smoothness
Konstantinos Oikonomidis, Jan Quan, Emanuel Laude et al.
Nonlinear transformers can perform inference-time feature learning
Naoki Nishikawa, Yujin Song, Kazusato Oko et al.
Nonparametric Identification of Latent Concepts
Yujia Zheng, Shaoan Xie, Kun Zhang
Nonparametric Modern Hopfield Models
Jerry Yao-Chieh Hu, Bo-Yu Chen, Dennis Wu et al.
Nonparametric Teaching for Graph Property Learners
Chen Zhang, Weixin Bu, Zeyi Ren et al.
Non-stationary Diffusion For Probabilistic Time Series Forecasting
Weiwei Ye, Zhuopeng Xu, Ning Gui
Non-stationary Online Learning for Curved Losses: Improved Dynamic Regret via Mixability
Yu-Jie Zhang, Peng Zhao, Masashi Sugiyama
Non-Stationary Predictions May Be More Informative: Exploring Pseudo-Labels with a Two-Phase Pattern of Training Dynamics
Hongbin Pei, Jingxin Hai, Yu Li et al.
No-Regret is not enough! Bandits with General Constraints through Adaptive Regret Minimization
Martino Bernasconi, Matteo Castiglioni, Andrea Celli
Normalizing Flows are Capable Generative Models
Shuangfei Zhai, Ruixiang Zhang, Preetum Nakkiran et al.
No Soundness in the Real World: On the Challenges of the Verification of Deployed Neural Networks
Attila Szász, Balázs Bánhelyi, Mark Jelasity
Not all solutions are created equal: An analytical dissociation of functional and representational similarity in deep linear neural networks
Lukas Braun, Erin Grant, Andrew Saxe
Not All Tokens Matter All The Time: Dynamic Token Aggregation Towards Efficient Detection Transformers
Jiacheng Cheng, Xiwen Yao, Xiang Yuan et al.
Not All Wrong is Bad: Using Adversarial Examples for Unlearning
Ali Ebrahimpour-Boroojeny, Hari Sundaram, Varun Chandrasekaran
No Task Left Behind: Isotropic Model Merging with Common and Task-Specific Subspaces
Daniel Marczak, Simone Magistri, Sebastian Cygert et al.
Novelty Detection in Reinforcement Learning with World Models
Geigh Zollicoffer, Kenneth Eaton, Jonathan Balloch et al.