Most Cited ICML "image autoencoders" Papers
5,975 papers found • Page 18 of 30
Conference
Banyan: Improved Representation Learning with Explicit Structure
Mattia Opper, Siddharth N
Edge-Colored Clustering in Hypergraphs: Beyond Minimizing Unsatisfied Edges
Alex Crane, Thomas Stanley, Blair D. Sullivan et al.
On a Neural Implementation of Brenier's Polar Factorization
Nina Vesseron, Marco Cuturi
ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning
Artavazd Maranjyan, El Mehdi Saad, Peter Richtarik et al.
DLP: Dynamic Layerwise Pruning in Large Language Models
Yuli Chen, Bo Cheng, Jiale Han et al.
The Role of Randomness in Stability
Max Hopkins, Shay Moran
MoMa: Modulating Mamba for Adapting Image Foundation Models to Video Recognition
Yuhuan Yang, Chaofan Ma, Zhenjie Mao et al.
A Theoretical Justification for Asymmetric Actor-Critic Algorithms
Gaspard Lambrechts, Damien Ernst, Aditya Mahajan
Adaptive Stabilization Based on Machine Learning for Column Generation
Yunzhuang Shen, Yuan Sun, Xiaodong Li et al.
PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning
Jaejun Lee, Minsung Hwang, Joyce Whang
DragSolver: A Multi-Scale Transformer for Real-World Automotive Drag Coefficient Estimation
Ye Liu, Yuntian Chen
OOD-Chameleon: Is Algorithm Selection for OOD Generalization Learnable?
Liangze Jiang, Damien Teney
Teaching Physical Awareness to LLMs through Sounds
Weiguo Wang, Andy Nie, Wenrui Zhou et al.
Automated Loss function Search for Class-imbalanced Node Classification
Xinyu Guo, KAI WU, Xiaoyu Zhang et al.
Enabling Optimal Decisions in Rehearsal Learning under CARE Condition
Wen-Bo Du, Hao-Yi Lei, Lue Tao et al.
MS$^3$D: A RG Flow-Based Regularization for GAN Training with Limited Data
Jian Wang, Xin Lan, Yuxin Tian et al.
Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processes
Bhargav Ganguly, Yang Xu, Vaneet Aggarwal
Distributed Conformal Prediction via Message Passing
Haifeng Wen, Hong XING, Osvaldo Simeone
Prediction via Shapley Value Regression
Amr Alkhatib, Roman Bresson, Henrik Boström et al.
WildChat-50M: A Deep Dive Into the Role of Synthetic Data in Post-Training
Benjamin Feuer, Chinmay Hegde
Pursuing Overall Welfare in Federated Learning through Sequential Decision Making
Seok-Ju Hahn, Gi-Soo Kim, Junghye Lee
Rich-Observation Reinforcement Learning with Continuous Latent Dynamics
Yuda Song, Lili Wu, Dylan Foster et al.
Overcoming Vocabulary Mismatch: Vocabulary-agnostic Teacher Guided Language Modeling
Haebin Shin, Lei Ji, Xiao Liu et al.
Topological Signatures of Adversaries in Multimodal Alignments
Minh Vu, Geigh Zollicoffer, Huy Mai et al.
Test-time Correlation Alignment
Linjing You, Jiabao Lu, Xiayuan Huang
A Contextual Combinatorial Bandit Approach to Negotiation
Yexin Li, Zhancun Mu, Siyuan Qi
A Theory for Conditional Generative Modeling on Multiple Data Sources
Rongzhen Wang, Yan Zhang, Chenyu Zheng et al.
QuanONet: Quantum Neural Operator with Application to Differential Equation
Ruocheng Wang, Zhuo Xia, Ge Yan et al.
Optimal Task Order for Continual Learning of Multiple Tasks
Ziyan Li, Naoki Hiratani
CursorCore: Assist Programming through Aligning Anything
Hao Jiang, Qi Liu, Rui Li et al.
Unisoma: A Unified Transformer-based Solver for Multi-Solid Systems
Shilong Tao, Zhe Feng, Haonan Sun et al.
A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning
Yaxin Hou, Yuheng Jia
Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model
Rachel Cummings, Alessandro Epasto, Jieming Mao et al.
A Statistical Framework for Data-dependent Retrieval-Augmented Models
Soumya Basu, Ankit Singh Rawat, Manzil Zaheer
Masked Generative Nested Transformers with Decode Time Scaling
Sahil Goyal, Debapriya Tula, Gagan Jain et al.
Variational Counterfactual Intervention Planning to Achieve Target Outcomes
Xin Wang, Shengfei Lyu, Luo Chi et al.
Fully Heteroscedastic Count Regression with Deep Double Poisson Networks
Spencer Young, Porter Jenkins, Longchao Da et al.
Deciphering RNA Secondary Structure Prediction: A Probabilistic K-Rook Matching Perspective
Cheng Tan, Zhangyang Gao, Hanqun CAO et al.
Scaling Value Iteration Networks to 5000 Layers for Extreme Long-Term Planning
Yuhui Wang, Qingyuan Wu, Dylan Ashley et al.
RestoreGrad: Signal Restoration Using Conditional Denoising Diffusion Models with Jointly Learned Prior
Ching-Hua Lee, Chouchang Yang, Jaejin Cho et al.
A Dynamic Algorithm for Weighted Submodular Cover Problem
Kiarash Banihashem, Samira Goudarzi, MohammadTaghi Hajiaghayi et al.
Learning multivariate Gaussians with imperfect advice
Arnab Bhattacharyya, Davin Choo, Philips George John et al.
Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks
Haoyu Li, Shichang Zhang, Longwen Tang et al.
Stacey: Promoting Stochastic Steepest Descent via Accelerated $\ell_p$-Smooth Nonconvex Optimization
Xinyu Luo, Cedar Site Bai, Bolian Li et al.
Distilling the Knowledge in Data Pruning
Emanuel Ben Baruch, Adam Botach, Igor Kviatkovsky et al.
Adjustment for Confounding using Pre-Trained Representations
Rickmer Schulte, David Rügamer, Thomas Nagler
ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks
Zhiyao Ren, Siyuan Liang, Aishan Liu et al.
Identifying biological perturbation targets through causal differential networks
Menghua Wu, Umesh Padia, Sean Murphy et al.
Explicit Preference Optimization: No Need for an Implicit Reward Model
Xiangkun Hu, Lemin Kong, Tong He et al.
Radio: Rate–Distortion Optimization for Large Language Model Compression
Sean I. Young
AutoGFM: Automated Graph Foundation Model with Adaptive Architecture Customization
Haibo Chen, Xin Wang, Zeyang Zhang et al.
Designing Cyclic Peptides via Harmonic SDE with Atom-Bond Modeling
Xiangxin Zhou, Mingyu Li, xiao yi et al.
Preference Learning for AI Alignment: a Causal Perspective
Katarzyna Kobalczyk, Mihaela van der Schaar
Statistical Query Hardness of Multiclass Linear Classification with Random Classification Noise
Ilias Diakonikolas, Mingchen Ma, Lisheng Ren et al.
M2PDE: Compositional Generative Multiphysics and Multi-component PDE Simulation
Tao Zhang, Zhenhai Liu, Feipeng Qi et al.
Bootstrapping Fisher Market Equilibrium and First-Price Pacing Equilibrium
Luofeng Liao, Christian Kroer
Monte-Carlo Tree Search with Uncertainty Propagation via Optimal Transport
Tuan Dam, Pascal Stenger, Lukas Schneider et al.
LEMoN: Label Error Detection using Multimodal Neighbors
Haoran Zhang, Aparna Balagopalan, Nassim Oufattole et al.
An Effective Dynamic Gradient Calibration Method for Continual Learning
Weichen Lin, Jiaxiang Chen, Ruomin Huang et al.
PAC-Bayes Analysis for Recalibration in Classification
Masahiro Fujisawa, Futoshi Futami
Do Not Mimic My Voice : Speaker Identity Unlearning for Zero-Shot Text-to-Speech
Taesoo Kim, Jinju Kim, Dongchan Kim et al.
Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals
Junyan Liu, ARNAB MAITI, Artin Tajdini et al.
Randomized Confidence Bounds for Stochastic Partial Monitoring
Maxime Heuillet, Ola Ahmad, Audrey Durand
Uniformly Stable Algorithms for Adversarial Training and Beyond
Jiancong Xiao, Jiawei Zhang, Zhi-Quan Luo et al.
Quantifying Memory Utilization with Effective State-Size
Rom N. Parnichkun, Neehal Tumma, Armin Thomas et al.
A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization
Nuojin Cheng, Leonard Papenmeier, Stephen Becker et al.
Preference Adaptive and Sequential Text-to-Image Generation
Ofir Nabati, Guy Tennenholtz, Chih-wei Hsu et al.
Falsification of Unconfoundedness by Testing Independence of Causal Mechanisms
Rickard K.A. Karlsson, Jesse H. Krijthe
Generalization in Federated Learning: A Conditional Mutual Information Framework
Ziqiao Wang, Cheng Long, Yongyi Mao
Statistically Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution
Elen Vardanyan, Sona Hunanyan, Tigran Galstyan et al.
Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation
Da Long, Zhitong Xu, Guang Yang et al.
Exploring Large Action Sets with Hyperspherical Embeddings using von Mises-Fisher Sampling
Walid Bendada, Guillaume Salha-Galvan, Romain Hennequin et al.
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective
Hechuan Wen, Tong Chen, Mingming Gong et al.
Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient
Hao Di, Haishan Ye, Yueling Zhang et al.
Navigating Scaling Laws: Compute Optimality in Adaptive Model Training
Sotiris Anagnostidis, Gregor Bachmann, Imanol Schlag et al.
Average Certified Radius is a Poor Metric for Randomized Smoothing
Chenhao Sun, Yuhao Mao, Mark Müller et al.
Two Tales of Single-Phase Contrastive Hebbian Learning
Rasmus Kjær Høier, Christopher Zach
Imitation Learning from a Single Temporally Misaligned Video
William Huey, Yuki (Huaxiaoyue) Wang, Anne Wu et al.
Propagation of Chaos for Mean-Field Langevin Dynamics and its Application to Model Ensemble
Atsushi Nitanda, Anzelle Lee, Damian Kai et al.
Unveiling Markov heads in Pretrained Language Models for Offline Reinforcement Learning
Wenhao Zhao, Qiushui Xu, Linjie Xu et al.
Making Hard Problems Easier with Custom Data Distributions and Loss Regularization: A Case Study in Modular Arithmetic
Eshika Saxena, Alberto Alfarano, Emily Wenger et al.
Criterion Collapse and Loss Distribution Control
Matthew J. Holland
Optimal Transfer Learning for Missing Not-at-Random Matrix Completion
Akhil Jalan, Yassir Jedra, Arya Mazumdar et al.
Fishers for Free? Approximating the Fisher Information Matrix by Recycling the Squared Gradient Accumulator
YuXin Li, Felix Dangel, Derek Tam et al.
An Instrumental Value for Data Production and its Application to Data Pricing
Rui Ai, Boxiang Lyu, Zhaoran Wang et al.
The Noisy Laplacian: a Threshold Phenomenon for Non-Linear Dimension Reduction
Alex Kokot, Octavian-Vlad Murad, Marina Meila
Improving Consistency Models with Generator-Augmented Flows
Thibaut Issenhuth, Sangchul Lee, Ludovic Dos Santos et al.
TVE: Learning Meta-attribution for Transferable Vision Explainer
Guanchu (Gary) Wang, Yu-Neng Chuang, Fan Yang et al.
Coarse-To-Fine Tensor Trains for Compact Visual Representations
Sebastian Loeschcke, Dan Wang, Christian Leth-Espensen et al.
Mixture of Experts Provably Detect and Learn the Latent Cluster Structure in Gradient-Based Learning
Ryotaro Kawata, Kohsei Matsutani, Yuri Kinoshita et al.
BOOD: Boundary-based Out-Of-Distribution Data Generation
Qilin Liao, Shuo Yang, Bo Zhao et al.
SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point Clouds
Ali Bahri, Moslem Yazdanpanah, Sahar Dastani Oghani et al.
Graph Adversarial Diffusion Convolution
Songtao Liu, Jinghui Chen, Tianfan Fu et al.
R3DM: Enabling Role Discovery and Diversity Through Dynamics Models in Multi-agent Reinforcement Learning
Harsh Goel, Mohammad Omama, Behdad Chalaki et al.
GenCO: Generating Diverse Designs with Combinatorial Constraints
Aaron Ferber, Arman Zharmagambetov, Taoan Huang et al.
Optimal Kernel Quantile Learning with Random Features
Caixing Wang, Xingdong Feng
AuPair: Golden Example Pairs for Code Repair
Aditi Mavalankar, Hassan Mansoor, Zita Marinho et al.
MD tree: a model-diagnostic tree grown on loss landscape
Yefan Zhou, Jianlong Chen, Qinxue Cao et al.
Total Variation Floodgate for Variable Importance Inference in Classification
Wenshuo Wang, Lucas Janson, Lihua Lei et al.
From Black Boxes to Transparent Minds: Evaluating and Enhancing the Theory of Mind in Multimodal Large Language Models
Xinyang Li, Siqi Liu, Bochao Zou et al.
Individual Fairness in Graph Decomposition
Kamesh Munagala, Govind S. Sankar
Knowledge Retention in Continual Model-Based Reinforcement Learning
Haotian Fu, Yixiang Sun, Michael L. Littman et al.
Adaptive Online Experimental Design for Causal Discovery
Muhammad Qasim Elahi, Lai Wei, Murat Kocaoglu et al.
Careful with that Scalpel: Improving Gradient Surgery with an EMA
Yu-Guan Hsieh, James Thornton, Eugene Ndiaye et al.
TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation
Ziang Zhou, Zhihao DING, Jieming Shi et al.
Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity
Quan Nguyen, Nishant Mehta, Cristóbal Guzmán
UniMate: A Unified Model for Mechanical Metamaterial Generation, Property Prediction, and Condition Confirmation
Wangzhi Zhan, Chen Jianpeng, Dongqi Fu et al.
ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints
Akhil Agnihotri, Rahul Jain, Haipeng Luo
Tackling Dimensional Collapse toward Comprehensive Universal Domain Adaptation
Hung-Chieh Fang, Po-Yi Lu, Hsuan-Tien (Tien) Lin
Distinguishing Cause from Effect with Causal Velocity Models
Johnny Xi, Hugh Dance, Peter Orbanz et al.
Multigroup Robustness
Lunjia Hu, Charlotte Peale, Judy Hanwen Shen
Deep Ridgelet Transform and Unified Universality Theorem for Deep and Shallow Joint-Group-Equivariant Machines
Sho Sonoda, Yuka Hashimoto, Isao Ishikawa et al.
AMPO: Active Multi Preference Optimization for Self-play Preference Selection
Taneesh Gupta, Rahul Madhavan, Xuchao Zhang et al.
Amortized Equation Discovery in Hybrid Dynamical Systems
Yongtuo Liu, Sara Magliacane, Miltiadis (Miltos) Kofinas et al.
Generalized Category Discovery via Reciprocal Learning and Class-Wise Distribution Regularization
Duo Liu, Zhiquan Tan, Linglan Zhao et al.
One Stone, Two Birds: Enhancing Adversarial Defense Through the Lens of Distributional Discrepancy
Jiacheng Zhang, Benjamin Rubinstein, Jingfeng Zhang et al.
Learning Representations of Instruments for Partial Identification of Treatment Effects
Jonas Schweisthal, Dennis Frauen, Maresa Schröder et al.
Deep Reinforcement Learning from Hierarchical Preference Design
Alexander Bukharin, Yixiao Li, Pengcheng He et al.
Generative Marginalization Models
Sulin Liu, Peter Ramadge, Ryan P. Adams
Optimal Exact Recovery in Semi-Supervised Learning: A Study of Spectral Methods and Graph Convolutional Networks
Haixiao Wang, Zhichao Wang
Simple Ingredients for Offline Reinforcement Learning
Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta et al.
Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares
Liangzu Peng, Wotao Yin
OmniBal: Towards Fast Instruction-Tuning for Vision-Language Models via Omniverse Computation Balance
Yongqiang Yao, Jingru Tan, Feizhao Zhang et al.
CoMemo: LVLMs Need Image Context with Image Memory
Shi Liu, Weijie Su, Xizhou Zhu et al.
A Causal World Model Underlying Next Token Prediction: Exploring GPT in a Controlled Environment
Raanan Yehezkel Rohekar, Yaniv Gurwicz, Sungduk Yu et al.
Generative Conditional Distributions by Neural (Entropic) Optimal Transport
Bao Nguyen, Binh Nguyen, Trung Hieu Nguyen et al.
Position: In-House Evaluation Is Not Enough. Towards Robust Third-Party Evaluation and Flaw Disclosure for General-Purpose AI
Shayne Longpre, Kevin Klyman, Ruth Elisabeth Appel et al.
Control and Realism: Best of Both Worlds in Layout-to-Image without Training
Bonan Li, Yinhan Hu, Songhua Liu et al.
INRFlow: Flow Matching for INRs in Ambient Space
Yuyang Wang, Anurag Ranjan, Joshua M Susskind et al.
Two Tickets are Better than One: Fair and Accurate Hiring Under Strategic LLM Manipulations
Lee Cohen, Connie Hong, Jack Hsieh et al.
Prediction-Powered Adaptive Shrinkage Estimation
Sida Li, Nikolaos Ignatiadis
Prediction Accuracy of Learning in Games : Follow-the-Regularized-Leader meets Heisenberg
Yi Feng, Georgios Piliouras, Xiao Wang
When Will Gradient Regularization Be Harmful?
Yang Zhao, Hao Zhang, Xiuyuan Hu
Privacy Profiles for Private Selection
Antti Koskela, Rachel Redberg, Yu-Xiang Wang
Adaptive Hierarchical Certification for Segmentation using Randomized Smoothing
Alaa Anani, Tobias Lorenz, Bernt Schiele et al.
MoRAgent: Parameter Efficient Agent Tuning with Mixture-of-Roles
Jing Han, Binwei Yan, Tianyu Guo et al.
A Variational Framework for Improving Naturalness in Generative Spoken Language Models
Li-Wei Chen, Takuya Higuchi, Zakaria Aldeneh et al.
Implicit Regularization for Tubal Tensor Factorizations via Gradient Descent
Santhosh Karnik, Anna Veselovska, Mark Iwen et al.
Accelerating Spectral Clustering under Fairness Constraints
Francesco Tonin, Alex Lambert, Johan Suykens et al.
Multiply Robust Estimation for Local Distribution Shifts with Multiple Domains
Steven Wilkins-Reeves, Xu Chen, Qi Ma et al.
A Tensor Decomposition Perspective on Second-order RNNs
Maude Lizaire, Michael Rizvi-Martel, Marawan Gamal et al.
Adaptive Accompaniment with ReaLchords
Yusong Wu, Tim Cooijmans, Kyle Kastner et al.
FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees
Fan Nie, Xiaotian Hou, Shuhang Lin et al.
Upcycling Text-to-Image Diffusion Models for Multi-Task Capabilities
Ruchika Chavhan, Abhinav Mehrotra, Malcolm Chadwick et al.
Efficient Diffusion Models for Symmetric Manifolds
Oren Mangoubi, Neil He, Nisheeth K. Vishnoi
SIMPLEMIX: Frustratingly Simple Mixing of Off- and On-policy Data in Language Model Preference Learning
Tianjian Li, Daniel Khashabi
Learning to Compile Programs to Neural Networks
Logan Weber, Jesse Michel, Alex Renda et al.
On the Provable Separation of Scales in Maximal Update Parameterization
Letong Hong, Zhangyang “Atlas” Wang
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
WATCH: Adaptive Monitoring for AI Deployments via Weighted-Conformal Martingales
Drew Prinster, Xing Han, Anqi Liu et al.
Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity
Ningyuan Huang, Miguel Sarabia, Abhinav Moudgil et al.
LRA-QViT: Integrating Low-Rank Approximation and Quantization for Robust and Efficient Vision Transformers
Beom Jin Kang, NamJoon Kim, Hyun Kim
A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networks
Varshita Kolipaka, Akshit Sinha, Debangan Mishra et al.
Occult: Optimizing Collaborative Communications across Experts for Accelerated Parallel MoE Training and Inference
Shuqing Luo, Pingzhi Li, Jie Peng et al.
Adaptive Exploration for Multi-Reward Multi-Policy Evaluation
Alessio Russo, Aldo Pacchiano
GenZSL: Generative Zero-Shot Learning Via Inductive Variational Autoencoder
Shiming Chen, Dingjie Fu, Salman Khan et al.
FuseUNet: A Multi-Scale Feature Fusion Method for U-like Networks
Quansong He, Xiangde Min, Kaishen Wang et al.
Triadic-OCD: Asynchronous Online Change Detection with Provable Robustness, Optimality, and Convergence
Yancheng Huang, Kai Yang, Zelin Zhu et al.
Counting in Small Transformers: The Delicate Interplay between Attention and Feed-Forward Layers
Freya Behrens, Luca Biggio, Lenka Zdeborová
Layer-wise Alignment: Examining Safety Alignment Across Image Encoder Layers in Vision Language Models
Saketh Bachu, Erfan Shayegani, Rohit Lal et al.
Closed-Loop Long-Horizon Robotic Planning via Equilibrium Sequence Modeling
Jinghan Li, Zhicheng Sun, Yadong Mu
TAROT: Targeted Data Selection via Optimal Transport
Lan Feng, Fan Nie, Yuejiang Liu et al.
Flow-of-Options: Diversified and Improved LLM Reasoning by Thinking Through Options
Lakshmi Nair, Ian Trase, J. Kim
The Butterfly Effect: Neural Network Training Trajectories Are Highly Sensitive to Initial Conditions
Gül Sena Altıntaş, Devin Kwok, Colin Raffel et al.
Improving the Variance of Differentially Private Randomized Experiments through Clustering
Adel Javanmard, Vahab Mirrokni, Jean Pouget-Abadie
Optimal Transport Barycenter via Nonconvex-Concave Minimax Optimization
Kaheon Kim, Rentian Yao, Changbo Zhu et al.
Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning
Joon Suk Huh, Kirthevasan Kandasamy
Sequence Compression Speeds Up Credit Assignment in Reinforcement Learning
Aditya A. Ramesh, Kenny Young, Louis Kirsch et al.
Deep Bayesian Filter for Bayes-Faithful Data Assimilation
Yuta Tarumi, Keisuke Fukuda, Shin-ichi Maeda
FIC-TSC: Learning Time Series Classification with Fisher Information Constraint
Xiwen Chen, Wenhui Zhu, Peijie Qiu et al.
Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning
Vicente Balmaseda, Bokun Wang, Lin et al.
Large Language Models are Demonstration Pre-Selectors for Themselves
Jiarui Jin, Yuwei Wu, Haoxuan Li et al.
Soup-of-Experts: Pretraining Specialist Models via Parameters Averaging
Pierre Ablin, Angelos Katharopoulos, Skyler Seto et al.
Understanding the Statistical Accuracy-Communication Trade-off in Personalized Federated Learning with Minimax Guarantees
Xin Yu, Zelin He, Ying Sun et al.
Learning Time-Varying Multi-Region Brain Communications via Scalable Markovian Gaussian Processes
Weihan Li, Yule Wang, Chengrui Li et al.
Adversarial Inception Backdoor Attacks against Reinforcement Learning
Ethan Rathbun, Alina Oprea, Christopher Amato
Better Locally Private Sparse Estimation Given Multiple Samples Per User
Yuheng Ma, Ke Jia, Hanfang Yang
Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective
Yang Chen, Cong Fang, Zhouchen Lin et al.
Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention
Stephan Rabanser, Ali Shahin Shamsabadi, Olive Franzese et al.
Smooth Min-Max Monotonic Networks
Christian Igel
No Free Lunch from Random Feature Ensembles: Scaling Laws and Near-Optimality Conditions
Benjamin Ruben, William Tong, Hamza Chaudhry et al.
Benchmarking Abstract and Reasoning Abilities Through A Theoretical Perspective
Qingchuan Ma, Yuhang Wu, Xiawu Zheng et al.
Regularized Langevin Dynamics for Combinatorial Optimization
Shengyu Feng, Yiming Yang
LapSum - One Method to Differentiate Them All: Ranking, Sorting and Top-k Selection
Łukasz Struski, Michal Bednarczyk, Igor Podolak et al.
Sparse Spectral Training and Inference on Euclidean and Hyperbolic Neural Networks
Jialin Zhao, Yingtao Zhang, Xinghang Li et al.
Position: All Current Generative Fidelity and Diversity Metrics are Flawed
Ossi Räisä, Boris van Breugel, Mihaela van der Schaar
IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic
Stefano Viel, Luca Viano, Volkan Cevher
Optimal Sensor Scheduling and Selection for Continuous-Discrete Kalman Filtering with Auxiliary Dynamics
Mohamad Al Ahdab, john leth, Zheng-Hua Tan
Strategic A/B testing via Maximum Probability-driven Two-armed Bandit
Yu Zhang, Shanshan Zhao, Bokui Wan et al.
Nesterov Method for Asynchronous Pipeline Parallel Optimization
Thalaiyasingam Ajanthan, Sameera Ramasinghe, Yan Zuo et al.
World Model Implanting for Test-time Adaptation of Embodied Agents
Minjong Yoo, Jinwoo Jang, Sihyung Yoon et al.
Offline Imitation from Observation via Primal Wasserstein State Occupancy Matching
Kai Yan, Alex Schwing, Yu-Xiong Wang
MALIBO: Meta-learning for Likelihood-free Bayesian Optimization
Jiarong Pan, Stefan Falkner, Felix Berkenkamp et al.
Learning from others' mistakes: Finetuning machine translation models with span-level error annotations
Lily Zhang, Hamid Dadkhahi, Mara Finkelstein et al.
Stochastic Encodings for Active Feature Acquisition
Alexander Norcliffe, Changhee Lee, Fergus Imrie et al.
Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts
Chengyi Cai, Zesheng Ye, Lei Feng et al.
Exogenous Isomorphism for Counterfactual Identifiability
Yikang Chen, Dehui du
Prospector Heads: Generalized Feature Attribution for Large Models & Data
Gautam Machiraju, Alexander Derry, Arjun Desai et al.
Robust ML Auditing using Prior Knowledge
Jade Garcia Bourrée, Augustin Godinot, Sayan Biswas et al.
Masked Face Recognition with Generative-to-Discriminative Representations
Shiming Ge, Weijia Guo, Chenyu Li et al.