Most Cited ICML "resource-efficient prompting" Papers
5,975 papers found • Page 18 of 30
Conference
Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts?
Huy Nguyen, Pedram Akbarian, Nhat Ho
Learning Adaptive and View-Invariant Vision Transformer for Real-Time UAV Tracking
Yongxin Li, Mengyuan Liu, You Wu et al.
PID: Prompt-Independent Data Protection Against Latent Diffusion Models
Ang Li, Yichuan Mo, Mingjie Li et al.
A Contextual Combinatorial Bandit Approach to Negotiation
Yexin Li, Zhancun Mu, Siyuan Qi
DiffStitch: Boosting Offline Reinforcement Learning with Diffusion-based Trajectory Stitching
Guanghe Li, Yixiang Shan, Zhengbang Zhu et al.
Privacy Preserving Adaptive Experiment Design
Jiachun Li, Kaining Shi, David Simchi-Levi
Combining Experimental and Historical Data for Policy Evaluation
Ting Li, Chengchun Shi, Qianglin Wen et al.
LoRAP: Transformer Sub-Layers Deserve Differentiated Structured Compression for Large Language Models
guangyan li, Yongqiang Tang, Wensheng Zhang
DiffFPR: Diffusion Prior for Oversampled Fourier Phase Retrieval
Ji Li, Chao Wang
Harnessing Neural Unit Dynamics for Effective and Scalable Class-Incremental Learning
Depeng Li, Tianqi Wang, Junwei Chen et al.
Compress Clean Signal from Noisy Raw Image: A Self-Supervised Approach
Zhihao Li, Yufei Wang, Alex Kot et al.
VQDNA: Unleashing the Power of Vector Quantization for Multi-Species Genomic Sequence Modeling
Siyuan Li, Zedong Wang, Zicheng Liu et al.
Emergent Representations of Program Semantics in Language Models Trained on Programs
Charles Jin, Martin Rinard
OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift
Lin Li, Yifei Wang, Chawin Sitawarin et al.
Improved Bounds for Pure Private Agnostic Learning: Item-Level and User-Level Privacy
Bo Li, Wei Wang, Peng Ye
$\bf{\Phi}_\textrm{Flow}$: Differentiable Simulations for PyTorch, TensorFlow and Jax
Philipp Holl, Nils Thuerey
The Good, The Bad, and Why: Unveiling Emotions in Generative AI
CHENG LI, Jindong Wang, Yixuan Zhang et al.
Two-Stage Shadow Inclusion Estimation: An IV Approach for Causal Inference under Latent Confounding and Collider Bias
Baohong Li, Anpeng Wu, Ruoxuan Xiong et al.
FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction
Zhonghang Li, Lianghao Xia, Yong Xu et al.
Towards efficient deep spiking neural networks construction with spiking activity based pruning
Yaxin Li, Qi Xu, Jiangrong Shen et al.
FedBAT: Communication-Efficient Federated Learning via Learnable Binarization
Shiwei Li, Wenchao Xu, Haozhao Wang et al.
Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process
Zichong Li, Qunzhi Xu, Zhenghao Xu et al.
Statistical Properties of Robust Satisficing
zhiyi li, Yunbei Xu, Ruohan Zhan
ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models
Ziniu Li, Tian Xu, Yushun Zhang et al.
IIANet: An Intra- and Inter-Modality Attention Network for Audio-Visual Speech Separation
Kai Li, Runxuan Yang, Fuchun Sun et al.
KernelWarehouse: Rethinking the Design of Dynamic Convolution
Chao Li, Anbang Yao
GeoReasoner: Geo-localization with Reasoning in Street Views using a Large Vision-Language Model
Ling Li, Yu Ye, Bingchuan Jiang et al.
Learning the Uncertainty Sets of Linear Control Systems via Set Membership: A Non-asymptotic Analysis
Yingying Li, Jing Yu, Lauren Conger et al.
Seesaw: Compensating for Nonlinear Reduction with Linear Computations for Private Inference
Fabing Li, Yuanhao Zhai, Shuangyu Cai et al.
Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks
Haoyu Li, Shichang Zhang, Longwen Tang et al.
From Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems
Xin Li, Jingdong Zhang, Qunxi Zhu et al.
EvoRainbow: Combining Improvements in Evolutionary Reinforcement Learning for Policy Search
Pengyi Li, Yan Zheng, Hongyao Tang et al.
Algorithmic Stability Unleashed: Generalization Bounds with Unbounded Losses
Shaojie Li, Bowei Zhu, Yong Liu
Receptive Fields As Experts in Convolutional Neural Architectures
Dongze Lian, Weihao Yu, Xinchao Wang
Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale Dataset
Shijie Lian, Ziyi Zhang, Hua Li et al.
Graph External Attention Enhanced Transformer
Jianqing Liang, Min Chen, Jiye Liang
Single-Trajectory Distributionally Robust Reinforcement Learning
Zhipeng Liang, Xiaoteng Ma, Jose Blanchet et al.
Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization
Jian Liang, Sheng, Zhengbo Wang et al.
On the Error-Propagation of Inexact Hotelling's Deflation for Principal Component Analysis
Fangshuo Liao, J. Lyle Kim, Cruz Barnum et al.
Bootstrapping Fisher Market Equilibrium and First-Price Pacing Equilibrium
Luofeng Liao, Christian Kroer
Graph Geometry-Preserving Autoencoders
Jungbin Lim, Jihwan Kim, Yonghyeon Lee et al.
Momentum Particle Maximum Likelihood
Jen Ning Lim, Juan Kuntz, Samuel Power et al.
An Effective Dynamic Gradient Calibration Method for Continual Learning
Weichen Lin, Jiaxiang Chen, Ruomin Huang et al.
Revisiting the Role of Language Priors in Vision-Language Models
Zhiqiu Lin, Xinyue Chen, Deepak Pathak et al.
Non-confusing Generation of Customized Concepts in Diffusion Models
Wang Lin, Jingyuan CHEN, Jiaxin Shi et al.
Structured Inverse-Free Natural Gradient Descent: Memory-Efficient & Numerically-Stable KFAC
Wu Lin, Felix Dangel, Runa Eschenhagen et al.
Robustness of Deep Learning for Accelerated MRI: Benefits of Diverse Training Data
Kang Lin, Reinhard Heckel
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency
Yuchao Lin, Jacob Helwig, Shurui Gui et al.
Graph-enhanced Large Language Models in Asynchronous Plan Reasoning
Fangru Lin, Emanuele La Malfa, Valentin Hofmann et al.
HGAP: Boosting Permutation Invariant and Permutation Equivariant in Multi-Agent Reinforcement Learning via Graph Attention Network
Bor Jiun Lin, Chun-Yi Lee
Parsimonious Learning-Augmented Approximations for Dense Instances of $\mathcal{NP}$-hard Problems
Evripidis Bampis, Bruno Escoffier, Michalis Xefteris
SparseTSF: Modeling Long-term Time Series Forecasting with *1k* Parameters
Shengsheng Lin, Weiwei Lin, Wentai Wu et al.
On Hypothesis Transfer Learning of Functional Linear Models
Haotian Lin, Matthew Reimherr
GeoAB: Towards Realistic Antibody Design and Reliable Affinity Maturation
Haitao Lin, Lirong Wu, Yufei Huang et al.
A Single-Loop Robust Policy Gradient Method for Robust Markov Decision Processes
Zhenwei Lin, Chenyu Xue, Qi Deng et al.
A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts
Huy Nguyen, Pedram Akbarian, TrungTin Nguyen et al.
Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency
Runqi Lin, Chaojian Yu, Bo Han et al.
Autonomous Sparse Mean-CVaR Portfolio Optimization
Yizun Lin, Yangyu Zhang, Zhao-Rong Lai et al.
More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms
Hossein Zakerinia, Amin Behjati, Christoph Lampert
Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification
Xixun Lin, Wenxiao Zhang, Fengzhao Shi et al.
PPFLOW: Target-Aware Peptide Design with Torsional Flow Matching
Haitao Lin, Odin Zhang, Huifeng Zhao et al.
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras
Tzu-Yuan Lin, Minghan Zhu, Maani Ghaffari
Position: A Call to Action for a Human-Centered AutoML Paradigm
Marius Lindauer, Florian Karl, Anne Klier et al.
Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
Levi Lingsch, Mike Yan Michelis, Emmanuel de Bézenac et al.
Scaling Tractable Probabilistic Circuits: A Systems Perspective
Anji Liu, Kareem Ahmed, Guy Van den Broeck
Graph Distillation with Eigenbasis Matching
Yang Liu, Deyu Bo, Chuan Shi
Adaptive Text Watermark for Large Language Models
Yepeng Liu, Yuheng Bu
Graph Adversarial Diffusion Convolution
Songtao Liu, Jinghui Chen, Tianfan Fu et al.
Zeroth-Order Methods for Constrained Nonconvex Nonsmooth Stochastic Optimization
Zhuanghua Liu, Cheng Chen, Luo Luo et al.
ESNet: Evolution and Succession Network for High-Resolution Salient Object Detection
Hongyu Liu, Runmin Cong, Hua Li et al.
Unifying Image Processing as Visual Prompting Question Answering
Yihao Liu, Xiangyu Chen, Xianzheng Ma et al.
The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks
Ziquan Liu, Yufei Cui, Yan Yan et al.
Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models
Songtao Liu, Hanjun Dai, Yue Zhao et al.
Decoding-time Realignment of Language Models
Tianlin Liu, Shangmin Guo, Leonardo Martins Bianco et al.
DIDI: Diffusion-Guided Diversity for Offline Behavioral Generation
Jinxin Liu, Xinghong Guo, Zifeng Zhuang et al.
Bidirectional Reciprocative Information Communication for Few-Shot Semantic Segmentation
Yuanwei Liu, Junwei Han, Xiwen Yao et al.
Unlock the Cognitive Generalization of Deep Reinforcement Learning via Granular Ball Representation
Jiashun Liu, Jianye Hao, Yi Ma et al.
PAPM: A Physics-aware Proxy Model for Process Systems
Pengwei Liu, Zhongkai Hao, Xingyu Ren et al.
ELTA: An Enhancer against Long-Tail for Aesthetics-oriented Models
Limin Liu, Shuai He, Anlong Ming et al.
On the Feasibility of Single-Pass Full-Capacity Learning in Linear Threshold Neurons with Binary Input Vectors
Ruipeng Liu, Borui He, Naveed Tahir et al.
Online Speculative Decoding
Xiaoxuan Liu, Lanxiang Hu, Peter Bailis et al.
Tuning-free Estimation and Inference of Cumulative Distribution Function under Local Differential Privacy
Yi Liu, Qirui Hu, Linglong Kong
Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion
Xuantong Liu, Tianyang Hu, Wenjia Wang et al.
Reason for Future, Act for Now: A Principled Architecture for Autonomous LLM Agents
Zhihan Liu, Hao Hu, Shenao Zhang et al.
Stereo Risk: A Continuous Modeling Approach to Stereo Matching
Ce Liu, Suryansh Kumar, Shuhang Gu et al.
Multi-Source Conformal Inference Under Distribution Shift
Yi Liu, Alexander Levis, Sharon-Lise Normand et al.
From Generalization Analysis to Optimization Designs for State Space Models
Fusheng Liu, Qianxiao Li
Short-Long Convolutions Help Hardware-Efficient Linear Attention to Focus on Long Sequences
Zicheng Liu, Siyuan Li, Li Wang et al.
Convergence of Online Learning Algorithm for a Mixture of Multiple Linear Regressions
Yujing Liu, Zhixin Liu, Lei Guo
Energy-Guided Diffusion Sampling for Offline-to-Online Reinforcement Learning
Xu-Hui Liu, Tian-Shuo Liu, Shengyi Jiang et al.
Moreau Envelope for Nonconvex Bi-Level Optimization: A Single-Loop and Hessian-Free Solution Strategy
Risheng Liu, Zhu Liu, Wei Yao et al.
Position: Foundation Agents as the Paradigm Shift for Decision Making
Xiaoqian Liu, Xingzhou Lou, Jianbin Jiao et al.
Amortized Equation Discovery in Hybrid Dynamical Systems
Yongtuo Liu, Sara Magliacane, Miltiadis (Miltos) Kofinas et al.
Floating Anchor Diffusion Model for Multi-motif Scaffolding
Ke Liu, Weian Mao, Shuaike Shen et al.
Class-Imbalanced Graph Learning without Class Rebalancing
Zhining Liu, Ruizhong Qiu, Zhichen Zeng et al.
Generative Marginalization Models
Sulin Liu, Peter Ramadge, Ryan P. Adams
Federated Representation Learning in the Under-Parameterized Regime
Renpu Liu, Cong Shen, Jing Yang
Causal Discovery via Conditional Independence Testing with Proxy Variables
Mingzhou Liu, Xinwei Sun, YU QIAO et al.
Perfect Alignment May be Poisonous to Graph Contrastive Learning
Jingyu Liu, Huayi Tang, Yong Liu
Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement
che liu, Zhongwei Wan, Cheng Ouyang et al.
Symmetric Matrix Completion with ReLU Sampling
Huikang Liu, Peng Wang, Longxiu Huang et al.
DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation
Qinshuo Liu, Zixin Wang, Xi'an Li et al.
High-Probability Bound for Non-Smooth Non-Convex Stochastic Optimization with Heavy Tails
Langqi Liu, Yibo Wang, Lijun Zhang
Language-Driven Cross-Modal Classifier for Zero-Shot Multi-Label Image Recognition
Yicheng Liu, Jie Wen, Chengliang Liu et al.
Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications
Jiashuo Liu, Jiayun Wu, Tianyu Wang et al.
Correlation-Induced Label Prior for Semi-Supervised Multi-Label Learning
Biao Liu, Ning Xu, Xiangyu Fang et al.
Causality Based Front-door Defense Against Backdoor Attack on Language Models
Yiran Liu, Xiaoang Xu, Zhiyi Hou et al.
Partial Multi-View Multi-Label Classification via Semantic Invariance Learning and Prototype Modeling
Chengliang Liu, Gehui Xu, Jie Wen et al.
Building Socially-Equitable Public Models
Yejia Liu, Jianyi Yang, Pengfei Li et al.
KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache
Zirui Liu, Jiayi Yuan, Hongye Jin et al.
Timer: Generative Pre-trained Transformers Are Large Time Series Models
Yong Liu, Haoran Zhang, Chenyu Li et al.
On the Last-Iterate Convergence of Shuffling Gradient Methods
Zijian Liu, Zhengyuan Zhou
Pairwise Alignment Improves Graph Domain Adaptation
Shikun Liu, Deyu Zou, Han Zhao et al.
Neural Operators with Localized Integral and Differential Kernels
Miguel Liu-Schiaffini, Julius Berner, Boris Bonev et al.
A Tensor Decomposition Perspective on Second-order RNNs
Maude Lizaire, Michael Rizvi-Martel, Marawan Gamal et al.
Restoring balance: principled under/oversampling of data for optimal classification
Emanuele Loffredo, Mauro Pastore, Simona Cocco et al.
Reparameterized Importance Sampling for Robust Variational Bayesian Neural Networks
Yunfei Long, Zilin Tian, Liguo Zhang et al.
Attention Meets Post-hoc Interpretability: A Mathematical Perspective
Gianluigi Lopardo, Frederic Precioso, Damien Garreau
Non-Vacuous Generalization Bounds for Large Language Models
Sanae Lotfi, Marc Finzi, Yilun Kuang et al.
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution
Aaron Lou, Chenlin Meng, Stefano Ermon
Optimal Differentially Private Model Training with Public Data
Andrew Lowy, Zeman Li, Tianjian Huang et al.
How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization
Andrew Lowy, Jonathan Ullman, Stephen Wright
Beyond Sole Strength: Customized Ensembles for Generalized Vision-Language Models
Zhihe Lu, Jiawang Bai, Xin Li et al.
HumanTOMATO: Text-aligned Whole-body Motion Generation
Shunlin Lu, Ling-Hao Chen, Ailing Zeng et al.
Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum
Tin Sum Cheng, Aurelien Lucchi, Anastasis Kratsios et al.
Position: Exploring the Robustness of Pipeline-Parallelism-Based Decentralized Training
Lin Lu, Chenxi Dai, Wangcheng Tao et al.
CATS: Enhancing Multivariate Time Series Forecasting by Constructing Auxiliary Time Series as Exogenous Variables
Jiecheng Lu, Xu Han, Sun et al.
WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
Xing Han Lù, Zdeněk Kasner, Siva Reddy
EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time
Shengyao Lu, Bang Liu, Keith Mills et al.
CauDiTS: Causal Disentangled Domain Adaptation of Multivariate Time Series
Junxin Lu, Shiliang Sun
FiT: Flexible Vision Transformer for Diffusion Model
Zeyu Lu, ZiDong Wang, Di Huang et al.
Probabilistic Routing for Graph-Based Approximate Nearest Neighbor Search
Kejing Lu, Chuan Xiao, Yoshiharu Ishikawa
OxyGenerator: Reconstructing Global Ocean Deoxygenation Over a Century with Deep Learning
Bin Lu, Ze Zhao, Luyu Han et al.
SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
Xudong LU, Aojun Zhou, Yuhui Xu et al.
Unveiling the Cycloid Trajectory of EM Iterations in Mixed Linear Regression
Zhankun Luo, Abolfazl Hashemi
OMPO: A Unified Framework for RL under Policy and Dynamics Shifts
Yu Luo, Tianying Ji, Fuchun Sun et al.
OLLIE: Imitation Learning from Offline Pretraining to Online Finetuning
Sheng Yue, Xingyuan Hua, Ju Ren et al.
Offline-Boosted Actor-Critic: Adaptively Blending Optimal Historical Behaviors in Deep Off-Policy RL
Yu Luo, Tianying Ji, Fuchun Sun et al.
Potential Based Diffusion Motion Planning
Yunhao Luo, Chen Sun, Josh Tenenbaum et al.
Cluster-Aware Similarity Diffusion for Instance Retrieval
Jifei Luo, Hantao Yao, Changsheng Xu
RoboMP$^2$: A Robotic Multimodal Perception-Planning Framework with Multimodal Large Language Models
Qi Lv, Hao Li, Xiang Deng et al.
Contamination-Resilient Anomaly Detection via Adversarial Learning on Partially-Observed Normal and Anomalous Data
Wenxi Lv, Qinliang Su, Hai Wan et al.
Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models
Qitan Lv, Jie Wang, Hanzhu Chen et al.
Efficient and Effective Time-Series Forecasting with Spiking Neural Networks
Changze Lv, Yansen Wang, Dongqi Han et al.
Cross-Domain Policy Adaptation by Capturing Representation Mismatch
Jiafei Lyu, Chenjia Bai, Jing-Wen Yang et al.
Sampling is as easy as keeping the consistency: convergence guarantee for Consistency Models
Junlong Lyu, Zhitang Chen, Shoubo Feng
Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation
Xinyu Ma, Xu Chu, Zhibang Yang et al.
Rethinking Decision Transformer via Hierarchical Reinforcement Learning
Yi Ma, Jianye Hao, Hebin Liang et al.
Better Locally Private Sparse Estimation Given Multiple Samples Per User
Yuheng Ma, Ke Jia, Hanfang Yang
Outlier-aware Slicing for Post-Training Quantization in Vision Transformer
Yuexiao Ma, Huixia Li, Xiawu Zheng et al.
X-Oscar: A Progressive Framework for High-quality Text-guided 3D Animatable Avatar Generation
Yiwei Ma, Zhekai Lin, Jiayi Ji et al.
Neighboring Perturbations of Knowledge Editing on Large Language Models
Jun-Yu Ma, Zhen-Hua Ling, Ningyu Zhang et al.
HarmonyDream: Task Harmonization Inside World Models
Haoyu Ma, Jialong Wu, Ningya Feng et al.
High-dimensional Linear Bandits with Knapsacks
Wanteng Ma, Dong Xia, Jiashuo Jiang
SyCoCa: Symmetrizing Contrastive Captioners with Attentive Masking for Multimodal Alignment
Ziping Ma, Furong Xu, Jian liu et al.
Correcting Diffusion-Based Perceptual Image Compression with Privileged End-to-End Decoder
Yiyang Ma, Wenhan Yang, Jiaying Liu
A Provable Decision Rule for Out-of-Distribution Detection
Xinsong Ma, Xin Zou, Weiwei Liu
Faithfulness Measurable Masked Language Models
Andreas Madsen, Siva Reddy, Sarath Chandar
On the Hardness of Probabilistic Neurosymbolic Learning
Jaron Maene, Vincent Derkinderen, Luc De Raedt
Split-and-Denoise: Protect large language model inference with local differential privacy
Peihua Mai, Ran Yan, Zhe Huang et al.
tinyBenchmarks: evaluating LLMs with fewer examples
Felipe Maia Polo, Lucas Weber, Leshem Choshen et al.
SCoRe: Submodular Combinatorial Representation Learning
Anay Majee, Suraj Kothawade, Krishnateja Killamsetty et al.
LASER: Linear Compression in Wireless Distributed Optimization
Ashok Vardhan Makkuva, Marco Bondaschi, Thijs Vogels et al.
Entropy-Reinforced Planning with Large Language Models for Drug Discovery
Xuefeng Liu, Chih-chan Tien, Peng Ding et al.
Auto-Regressive Next-Token Predictors are Universal Learners
Eran Malach
Self-Composing Policies for Scalable Continual Reinforcement Learning
Mikel Malagón, Josu Ceberio, Jose A Lozano
Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks
Stefano Mannelli, Yaraslau Ivashynka, Andrew Saxe et al.
Submodular framework for structured-sparse optimal transport
Piyushi Manupriya, Pratik Kumar Jawanpuria, Karthik Gurumoorthy et al.
Large Language Models are Geographically Biased
Rohin Manvi, Samar Khanna, Marshall Burke et al.
Position: Graph Foundation Models Are Already Here
Haitao Mao, Zhikai Chen, Wenzhuo Tang et al.
Towards General Neural Surrogate Solvers with Specialized Neural Accelerators
Chenkai Mao, Robert Lupoiu, Tianxiang Dai et al.
$H$-Consistency Guarantees for Regression
Anqi Mao, Mehryar Mohri, Yutao Zhong
Regression with Multi-Expert Deferral
Anqi Mao, Mehryar Mohri, Yutao Zhong
No-Regret Reinforcement Learning in Smooth MDPs
Davide Maran, Alberto Maria Metelli, Matteo Papini et al.
Keep the Momentum: Conservation Laws beyond Euclidean Gradient Flows
Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré
Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling
Ivan Marisca, Cesare Alippi, Filippo Maria Bianchi
Convergence and Trade-Offs in Riemannian Gradient Descent and Riemannian Proximal Point
David Martínez-Rubio, Christophe Roux, Sebastian Pokutta
Using AI Uncertainty Quantification to Improve Human Decision-Making
Laura Marusich, Jonathan Bakdash, Yan Zhou et al.
On the Tractability of SHAP Explanations under Markovian Distributions
Reda Marzouk, De la Higuera
On the Consistency of Kernel Methods with Dependent Observations
Pierre-François Massiani, Sebastian Trimpe, Friedrich Solowjow
Delving into Differentially Private Transformer
Youlong Ding, Xueyang Wu, Yining meng et al.
Deep Fusion: Efficient Network Training via Pre-trained Initializations
Hanna Mazzawi, Xavi Gonzalvo, Michael Wunder et al.
Roping in Uncertainty: Robustness and Regularization in Markov Games
Jeremy McMahan, Giovanni Artiglio, Qiaomin Xie
IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generation
Luke Melas-Kyriazi, Iro Laina, Christian Rupprecht et al.
O$n$ Learning Deep O($n$)-Equivariant Hyperspheres
Pavlo Melnyk, Michael Felsberg, Mårten Wadenbäck et al.
Position: Tensor Networks are a Valuable Asset for Green AI
Eva Memmel, Clara Menzen, Jetze Schuurmans et al.
OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization
Xiang Meng, Shibal Ibrahim, Kayhan Behdin et al.
Physics-Informed Neural Network Policy Iteration: Algorithms, Convergence, and Verification
Yiming Meng, Ruikun Zhou, Amartya Mukherjee et al.
The Illusion of State in State-Space Models
William Merrill, Jackson Petty, Ashish Sabharwal
Superposition Prompting: Improving and Accelerating Retrieval-Augmented Generation
Thomas Merth, Qichen Fu, Mohammad Rastegari et al.
Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics
Siqi Miao, Zhiyuan Lu, Mia Liu et al.
Rethinking Independent Cross-Entropy Loss For Graph-Structured Data
Rui Miao, Kaixiong Zhou, Yili Wang et al.
Rethinking Momentum Knowledge Distillation in Online Continual Learning
Nicolas MICHEL, Maorong Wang, Ling Xiao et al.
Efficient World Models with Context-Aware Tokenization
Vincent Micheli, Eloi Alonso, François Fleuret
CLIPZyme: Reaction-Conditioned Virtual Screening of Enzymes
Peter Mikhael, Itamar Chinn, Regina Barzilay
Can Implicit Bias Imply Adversarial Robustness?
Hancheng Min, Rene Vidal
Understanding Retrieval-Augmented Task Adaptation for Vision-Language Models
Yifei Ming, Sharon Li
RODEO: Robust Outlier Detection via Exposing Adaptive Out-of-Distribution Samples
Hossein Mirzaei, Mohammad Jafari Varnousfaderani, Hamid Reza Dehbashi et al.
Prodigy: An Expeditiously Adaptive Parameter-Free Learner
Konstantin Mishchenko, Aaron Defazio
From Inverse Optimization to Feasibility to ERM
Saurabh Mishra, Anant Raj, Sharan Vaswani