Most Cited ICML "spectral coefficient learning" Papers
5,975 papers found • Page 19 of 30
Conference
DistiLLM: Towards Streamlined Distillation for Large Language Models
Jongwoo Ko, Sungnyun Kim, Tianyi Chen et al.
Estimating Barycenters of Distributions with Neural Optimal Transport
Alexander Kolesov, Petr Mokrov, Igor Udovichenko et al.
The Computational Complexity of Finding Second-Order Stationary Points
Andreas Kontogiannis, Vasilis Pollatos, Sotiris Kanellopoulos et al.
KISA: A Unified Keyframe Identifier and Skill Annotator for Long-Horizon Robotics Demonstrations
Longxin Kou, Fei Ni, Yan Zheng et al.
Understanding the Effects of Iterative Prompting on Truthfulness
Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju
No Free Prune: Information-Theoretic Barriers to Pruning at Initialization
Tanishq Kumar, Kevin Luo, Mark Sellke
Privately Learning Smooth Distributions on the Hypercube by Projections
Clément Lalanne, Sébastien Gadat
Single-Model Attribution of Generative Models Through Final-Layer Inversion
Mike Laszkiewicz, Jonas Ricker, Johannes Lederer et al.
Towards Understanding Inductive Bias in Transformers: A View From Infinity
Itay Lavie, Guy Gur-Ari, Zohar Ringel
Generalized Sobolev Transport for Probability Measures on a Graph
Tam Le, Truyen Nguyen, Kenji Fukumizu
Robust Inverse Graphics via Probabilistic Inference
Tuan Anh Le, Pavel Sountsov, Matthew Hoffman et al.
Run-Time Task Composition with Safety Semantics
Kevin Leahy, Makai Mann, Zachary Serlin
Stationary Latent Weight Inference for Unreliable Observations from Online Test-Time Adaptation
Jae-Hong Lee, Joon Hyuk Chang
Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks
Hojoon Lee, Hyeonseo Cho, Hyunseung Kim et al.
Fundamental Benefit of Alternating Updates in Minimax Optimization
Jaewook Lee, Hanseul Cho, Chulhee Yun
SelMatch: Effectively Scaling Up Dataset Distillation via Selection-Based Initialization and Partial Updates by Trajectory Matching
Yongmin Lee, Hye Won Chung
Pausing Policy Learning in Non-stationary Reinforcement Learning
Hyunin Lee, Ming Jin, Javad Lavaei et al.
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective
Soo Yong Lee, Sunwoo Kim, Fanchen Bu et al.
Supervised Matrix Factorization: Local Landscape Analysis and Applications
Joowon Lee, Hanbaek Lyu, Weixin Yao
Defining Neural Network Architecture through Polytope Structures of Datasets
Sangmin Lee, Abbas Mammadov, Jong Chul YE
StrWAEs to Invariant Representations
Hyunjong Lee, Yedarm Seong, Sungdong Lee et al.
Binning as a Pretext Task: Improving Self-Supervised Learning in Tabular Domains
Kyungeun Lee, Ye Seul Sim, Hye-Seung Cho et al.
Robust Optimization in Protein Fitness Landscapes Using Reinforcement Learning in Latent Space
Minji Lee, Luiz Felipe Vecchietti, Hyunkyu Jung et al.
Improving Gradient-Guided Nested Sampling for Posterior Inference
Pablo Lemos, Nikolay Malkin, Will Handley et al.
Eluder-based Regret for Stochastic Contextual MDPs
Orin Levy, Asaf Cassel, Alon Cohen et al.
Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms
Yuchen Li, Laura Balzano, Deanna Needell et al.
Critical windows: non-asymptotic theory for feature emergence in diffusion models
Marvin Li, Sitan Chen
Completing Visual Objects via Bridging Generation and Segmentation
Xiang Li, Yinpeng Chen, Chung-Ching Lin et al.
Evolving Subnetwork Training for Large Language Models
hanqi li, Lu Chen, Da Ma et al.
ExCP: Extreme LLM Checkpoint Compression via Weight-Momentum Joint Shrinking
Wenshuo Li, Xinghao Chen, Han Shu et al.
Two-sided Competing Matching Recommendation Markets With Quota and Complementary Preferences Constraints
Yuantong Li, Guang Cheng, Xiaowu Dai
Full-Atom Peptide Design based on Multi-modal Flow Matching
Jiahan Li, Chaoran Cheng, Zuofan Wu et al.
FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning
Wenzhe Li, Zihan Ding, Seth Karten et al.
Debiased Distribution Compression
Lingxiao Li, Raaz Dwivedi, Lester Mackey
RL-CFR: Improving Action Abstraction for Imperfect Information Extensive-Form Games with Reinforcement Learning
Boning Li, Zhixuan Fang, Longbo Huang
Graph Structure Extrapolation for Out-of-Distribution Generalization
Xiner Li, Shurui Gui, Youzhi Luo et al.
Q-Probe: A Lightweight Approach to Reward Maximization for Language Models
Kenneth Li, Samy Jelassi, Hugh Zhang et al.
Promises and Pitfalls of Generative Masked Language Modeling: Theoretical Framework and Practical Guidelines
Yuchen Li, Alexandre Kirchmeyer, Aashay Mehta et al.
Neural Collapse in Multi-label Learning with Pick-all-label Loss
Pengyu Li, Xiao Li, Yutong Wang et al.
A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing
Chengrui Li, Weihan Li, Yule Wang et al.
A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective
Baohong Li, Haoxuan Li, Anpeng Wu et al.
Enhancing Class-Imbalanced Learning with Pre-Trained Guidance through Class-Conditional Knowledge Distillation
Lan Li, Xin-Chun Li, Han-Jia Ye et al.
Measuring Stochastic Data Complexity with Boltzmann Influence Functions
Nathan Ng, Roger Grosse, Marzyeh Ghassemi
Concentration Inequalities for General Functions of Heavy-Tailed Random Variables
Shaojie Li, Yong Liu
Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts?
Huy Nguyen, Pedram Akbarian, Nhat Ho
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.
Combining Experimental and Historical Data for Policy Evaluation
Ting Li, Chengchun Shi, Qianglin Wen et al.
DiffFPR: Diffusion Prior for Oversampled Fourier Phase Retrieval
Ji Li, Chao Wang
Compress Clean Signal from Noisy Raw Image: A Self-Supervised Approach
Zhihao Li, Yufei Wang, Alex Kot et al.
Emergent Representations of Program Semantics in Language Models Trained on Programs
Charles Jin, Martin Rinard
Improved Bounds for Pure Private Agnostic Learning: Item-Level and User-Level Privacy
Bo Li, Wei Wang, Peng Ye
The Good, The Bad, and Why: Unveiling Emotions in Generative AI
CHENG LI, Jindong Wang, Yixuan Zhang et al.
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.
Seesaw: Compensating for Nonlinear Reduction with Linear Computations for Private Inference
Fabing Li, Yuanhao Zhai, Shuangyu Cai et al.
From Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems
Xin Li, Jingdong Zhang, Qunxi Zhu 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
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.
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.
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.
Graph-enhanced Large Language Models in Asynchronous Plan Reasoning
Fangru Lin, Emanuele La Malfa, Valentin Hofmann et al.
SparseTSF: Modeling Long-term Time Series Forecasting with *1k* Parameters
Shengsheng Lin, Weiwei Lin, Wentai Wu et al.
GeoAB: Towards Realistic Antibody Design and Reliable Affinity Maturation
Haitao Lin, Lirong Wu, Yufei Huang 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.
Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification
Xixun Lin, Wenxiao Zhang, Fengzhao Shi et al.
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras
Tzu-Yuan Lin, Minghan Zhu, Maani Ghaffari
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
Zeroth-Order Methods for Constrained Nonconvex Nonsmooth Stochastic Optimization
Zhuanghua Liu, Cheng Chen, Luo Luo 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.
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.
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.
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
Perfect Alignment May be Poisonous to Graph Contrastive Learning
Jingyu Liu, Huayi Tang, Yong Liu
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.
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.
Pairwise Alignment Improves Graph Domain Adaptation
Shikun Liu, Deyu Zou, Han Zhao et al.
Restoring balance: principled under/oversampling of data for optimal classification
Emanuele Loffredo, Mauro Pastore, Simona Cocco et al.
Optimal Differentially Private Model Training with Public Data
Andrew Lowy, Zeman Li, Tianjian Huang 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.
CATS: Enhancing Multivariate Time Series Forecasting by Constructing Auxiliary Time Series as Exogenous Variables
Jiecheng Lu, Xu Han, Sun et al.
EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time
Shengyao Lu, Bang Liu, Keith Mills 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.
OLLIE: Imitation Learning from Offline Pretraining to Online Finetuning
Sheng Yue, Xingyuan Hua, Ju Ren et al.
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.
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
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
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
Correcting Diffusion-Based Perceptual Image Compression with Privileged End-to-End Decoder
Yiyang Ma, Wenhan Yang, Jiaying Liu
Faithfulness Measurable Masked Language Models
Andreas Madsen, Siva Reddy, Sarath Chandar
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.
Self-Composing Policies for Scalable Continual Reinforcement Learning
Mikel Malagón, Josu Ceberio, Jose A Lozano
Position: Graph Foundation Models Are Already Here
Haitao Mao, Zhikai Chen, Wenzhuo Tang et al.
$H$-Consistency Guarantees for Regression
Anqi Mao, Mehryar Mohri, Yutao Zhong
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
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
O$n$ Learning Deep O($n$)-Equivariant Hyperspheres
Pavlo Melnyk, Michael Felsberg, Mårten Wadenbäck et al.
OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization
Xiang Meng, Shibal Ibrahim, Kayhan Behdin 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.
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
Can Implicit Bias Imply Adversarial Robustness?
Hancheng Min, Rene Vidal
From Inverse Optimization to Feasibility to ERM
Saurabh Mishra, Anant Raj, Sharan Vaswani
TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors
Yichuan Mo, Hui Huang, Mingjie Li et al.
Language Models with Conformal Factuality Guarantees
Christopher Mohri, Tatsunori Hashimoto
Slot Abstractors: Toward Scalable Abstract Visual Reasoning
Shanka Subhra Mondal, Jonathan Cohen, Taylor Webb
Causal Representation Learning Made Identifiable by Grouping of Observational Variables
Hiroshi Morioka, Aapo Hyvarinen
Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs
Chandra Mouli Sekar, Danielle Robinson, Shima Alizadeh et al.
SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States
Noga Mudrik, Gal Mishne, Adam Charles
Truly No-Regret Learning in Constrained MDPs
Adrian Müller, Pragnya Alatur, Volkan Cevher et al.
Optimal bounds for $\ell_p$ sensitivity sampling via $\ell_2$ augmentation
Alexander Munteanu, Simon Omlor
Turnstile $\ell_p$ leverage score sampling with applications
Alexander Munteanu, Simon Omlor
Factored-Reward Bandits with Intermediate Observations
Marco Mussi, Simone Drago, Marcello Restelli et al.
Best Arm Identification for Stochastic Rising Bandits
Marco Mussi, Alessandro Montenegro, Francesco Trovò et al.
PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect
Lokesh Nagalapatti, Pranava Singhal, Avishek Ghosh et al.
Density Ratio Estimation with Doubly Strong Robustness
Ryosuke Nagumo, Hironori Fujisawa
On Least Square Estimation in Softmax Gating Mixture of Experts
Huy Nguyen, Nhat Ho, Alessandro Rinaldo
PIDformer: Transformer Meets Control Theory
Tam Nguyen, Cesar Uribe, Tan Nguyen et al.
Differentially private exact recovery for stochastic block models
Dung Nguyen, Anil Vullikanti
How Transformers Learn Causal Structure with Gradient Descent
Eshaan Nichani, Alex Damian, Jason Lee
Understanding the Impact of Introducing Constraints at Inference Time on Generalization Error
Masaaki Nishino, Kengo Nakamura, Norihito Yasuda
Test-Time Model Adaptation with Only Forward Passes
Shuaicheng Niu, Chunyan Miao, Guohao Chen et al.
Latent Optimal Paths by Gumbel Propagation for Variational Bayesian Dynamic Programming
Xinlei Niu, Christian Walder, Jing Zhang et al.
$f$-Divergence Based Classification: Beyond the Use of Cross-Entropy
Nicola Novello, Andrea Tonello
In value-based deep reinforcement learning, a pruned network is a good network
Johan Obando Ceron, Aaron Courville, Pablo Samuel Castro
The Perception-Robustness Tradeoff in Deterministic Image Restoration
Guy Ohayon, Tomer Michaeli, Michael Elad
Linear Explanations for Individual Neurons
Tuomas Oikarinen, Lily Weng
Adaptive Proximal Gradient Methods Are Universal Without Approximation
Konstantinos Oikonomidis, Emanuel Laude, Puya Latafat et al.
Deep Stochastic Mechanics
Elena Orlova, Aleksei Ustimenko, Ruoxi Jiang et al.
Variational Linearized Laplace Approximation for Bayesian Deep Learning
Luis A. Ortega, Simon Rodriguez Santana, Daniel Hernández-Lobato
Differentiable Mapper for Topological Optimization of Data Representation
Ziyad Oulhaj, Mathieu Carrière, Bertrand Michel
Implicit Representations via Operator Learning
Sourav Pal, Harshavardhan Adepu, Clinton Wang et al.
Bayesian Program Learning by Decompiling Amortized Knowledge
Alessandro Palmarini, Christopher Lucas, Siddharth N
$S^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
Zijie Pan, Yushan Jiang, Sahil Garg et al.
Feedback Loops With Language Models Drive In-Context Reward Hacking
Alexander Pan, Erik Jones, Meena Jagadeesan et al.
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
Theodore Papamarkou, Maria Skoularidou, Konstantina Palla et al.
The Linear Representation Hypothesis and the Geometry of Large Language Models
Kiho Park, Yo Joong Choe, Victor Veitch
Foundation Policies with Hilbert Representations
Seohong Park, Tobias Kreiman, Sergey Levine
SignSGD with Federated Defense: Harnessing Adversarial Attacks through Gradient Sign Decoding
Chanho Park, Namyoon Lee
Optimal Ridge Regularization for Out-of-Distribution Prediction
Pratik Patil, Jin-Hong Du, Ryan Tibshirani
LPGD: A General Framework for Backpropagation through Embedded Optimization Layers
Anselm Paulus, Georg Martius, Vit Musil
Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces
Brahma Pavse, Matthew Zurek, Yudong Chen et al.
Graph Automorphism Group Equivariant Neural Networks
Edward Pearce-Crump, William J. Knottenbelt
BetterV: Controlled Verilog Generation with Discriminative Guidance
Zehua Pei, Huiling Zhen, Mingxuan Yuan et al.
Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural Networks
Amit Peleg, Matthias Hein
Knowledge Distillation with Auxiliary Variable
Bo Peng, zhen fang, Guangquan Zhang et al.
UPAM: Unified Prompt Attack in Text-to-Image Generation Models Against Both Textual Filters and Visual Checkers
Duo Peng, Qiuhong Ke, Jun Liu
Pragmatic Feature Preferences: Learning Reward-Relevant Preferences from Human Input
Andi Peng, Yuying Sun, Tianmin Shu et al.
UPOCR: Towards Unified Pixel-Level OCR Interface
Dezhi Peng, Zhenhua Yang, Jiaxin Zhang et al.
Solving Hierarchical Information-Sharing Dec-POMDPs: An Extensive-Form Game Approach
Johan Peralez, Aurélien Delage, Olivier Buffet et al.
The Relative Value of Prediction in Algorithmic Decision Making
Juan Perdomo
Prompting a Pretrained Transformer Can Be a Universal Approximator
Aleksandar Petrov, Phil Torr, Adel Bibi
Transport of Algebraic Structure to Latent Embeddings
Samuel Pfrommer, Brendon G. Anderson, Somayeh Sojoudi
Adaptive Conformal Inference by Betting
Aleksandr Podkopaev, Darren Xu, Kuang-chih Lee
Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling
Danil Provodin, Maurits Kaptein, Mykola Pechenizkiy
Unsupervised Domain Adaptation for Anatomical Structure Detection in Ultrasound Images
Bin Pu, Xingguo Lv, Jiewen Yang et al.
Learning to Remove Cuts in Integer Linear Programming
Pol Puigdemont, EFSTRATIOS PANTELEIMON SKOULAKIS, Grigorios Chrysos et al.
ByMI: Byzantine Machine Identification with False Discovery Rate Control
Chengde Qian, Mengyuan Wang, Haojie Ren et al.
Efficient Non-stationary Online Learning by Wavelets with Applications to Online Distribution Shift Adaptation
Yu-Yang Qian, Peng Zhao, Yu-Jie Zhang et al.
Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints
Dan Qiao, Yu-Xiang Wang
Accurate LoRA-Finetuning Quantization of LLMs via Information Retention
Haotong Qin, Xudong Ma, Xingyu Zheng et al.
Feasible Reachable Policy Iteration
Shentao Qin, Yujie Yang, Yao Mu et al.
Learning High-Order Relationships of Brain Regions
Weikang Qiu, Huangrui Chu, Selena Wang et al.
To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO
Zi-Hao Qiu, Siqi Guo, Mao Xu et al.
Compute Better Spent: Replacing Dense Layers with Structured Matrices
Shikai Qiu, Andres Potapczynski, Marc Finzi et al.
MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space
Yanru Qu, Keyue Qiu, Yuxuan Song et al.