Most Cited ICML "active vision" Papers
5,975 papers found • Page 23 of 30
Conference
Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
Kaiwen Xue, Yuhao Zhou, Shen Nie et al.
Sparse Dimensionality Reduction Revisited
Mikael Møller Høgsgaard, Lior Kamma, Kasper Green Larsen et al.
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization
Jiayi Wang, Shiqiang Wang, Rong-Rong Chen et al.
Subhomogeneous Deep Equilibrium Models
Pietro Sittoni, Francesco Tudisco
Speech Self-Supervised Learning Using Diffusion Model Synthetic Data
Heting Gao, Kaizhi Qian, Junrui Ni et al.
RoboDreamer: Learning Compositional World Models for Robot Imagination
Siyuan Zhou, Yilun Du, Jiaben Chen et al.
ContPhy: Continuum Physical Concept Learning and Reasoning from Videos
Zhicheng Zheng, Xin Yan, Zhenfang Chen et al.
3D-VLA: A 3D Vision-Language-Action Generative World Model
Haoyu Zhen, Xiaowen Qiu, Peihao Chen et al.
RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation
Yufei Wang, Zhou Xian, Feng Chen et al.
Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models
Didi Zhu, Zhongyi Sun, Zexi Li et al.
Compositional Image Decomposition with Diffusion Models
Jocelin Su, Nan Liu, Yanbo Wang et al.
Diffusion Rejection Sampling
Byeonghu Na, Yeongmin Kim, Minsang Park et al.
Information-Directed Pessimism for Offline Reinforcement Learning
Alec Koppel, Sujay Bhatt, Jiacheng Guo et al.
Exploring the Enigma of Neural Dynamics Through A Scattering-Transform Mixer Landscape for Riemannian Manifold
Tingting Dan, Ziquan Wei, Won Hwa Kim et al.
Partial Optimality in the Linear Ordering Problem
David Stein, Bjoern Andres
Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials
Jonathan Scott, Aine E Cahill
Differentially Private Domain Adaptation with Theoretical Guarantees
Raef Bassily, Corinna Cortes, Anqi Mao et al.
Differentially Private Worst-group Risk Minimization
Xinyu Zhou, Raef Bassily
Time Series Diffusion in the Frequency Domain
Jonathan Crabbé, Nicolas Huynh, Jan Stanczuk et al.
FreeBind: Free Lunch in Unified Multimodal Space via Knowledge Fusion
Zehan Wang, Ziang Zhang, xize cheng et al.
Position: Optimization in SciML Should Employ the Function Space Geometry
Johannes Müller, Marius Zeinhofer
Memory Efficient Neural Processes via Constant Memory Attention Block
Leo Feng, Frederick Tung, Hossein Hajimirsadeghi et al.
Box Facets and Cut Facets of Lifted Multicut Polytopes
Lucas Fabian Naumann, Jannik Irmai, Shengxian Zhao et al.
Improving Computational Complexity in Statistical Models with Local Curvature Information
Pedram Akbarian, Tongzheng Ren, Jiacheng Zhuo et al.
Online Algorithms with Uncertainty-Quantified Predictions
Bo Sun, Jerry Huang, Nicolas Christianson et al.
A Statistical Framework for Data-dependent Retrieval-Augmented Models
Soumya Basu, Ankit Singh Rawat, Manzil Zaheer
A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks
Nicholas Monath, Will Grathwohl, Michael Boratko et al.
Trained Random Forests Completely Reveal your Dataset
Julien Ferry, Ricardo Fukasawa, Timothée Pascal et al.
Generalization Analysis of Deep Non-linear Matrix Completion
Antoine Ledent, Rodrigo Alves
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers
Md Shamim Hussain, Mohammed Zaki, Dharmashankar Subramanian
R2E: Turning any Github Repository into a Programming Agent Environment
Naman Jain, Manish Shetty Molahalli, Tianjun Zhang et al.
Enhancing Value Function Estimation through First-Order State-Action Dynamics in Offline Reinforcement Learning
Yun-Hsuan Lien, Ping-Chun Hsieh, Tzu-Mao Li et al.
Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning
Yen-Ju Chen, Nai-Chieh Huang, Ching-pei Lee et al.
Verification of Machine Unlearning is Fragile
Binchi Zhang, Zihan Chen, Cong Shen et al.
Towards Certified Unlearning for Deep Neural Networks
Binchi Zhang, Yushun Dong, Tianhao Wang et al.
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents
Yilun Xu, Gabriele Corso, Tommi Jaakkola et al.
Dirichlet Flow Matching with Applications to DNA Sequence Design
Hannes Stärk, Bowen Jing, Chenyu Wang et al.
Reward Shaping for Reinforcement Learning with An Assistant Reward Agent
Haozhe Ma, Kuankuan Sima, Thanh Vinh Vo et al.
Human Alignment of Large Language Models through Online Preference Optimisation
Daniele Calandriello, Zhaohan Guo, REMI MUNOS et al.
Flora: Low-Rank Adapters Are Secretly Gradient Compressors
Yongchang Hao, Yanshuai Cao, Lili Mou
Expressivity and Generalization: Fragment-Biases for Molecular GNNs
Tom Wollschläger, Niklas Kemper, Leon Hetzel et al.
SelfIE: Self-Interpretation of Large Language Model Embeddings
Haozhe Chen, Carl Vondrick, Chengzhi Mao
Listenable Maps for Audio Classifiers
Francesco Paissan, Mirco Ravanelli, Cem Subakan
QBMK: Quantum-based Matching Kernels for Un-attributed Graphs
Lu Bai, Lixin Cui, Ming Li et al.
Unsupervised Parameter-free Simplicial Representation Learning with Scattering Transforms
Hiren Madhu, Sravanthi Gurugubelli, Sundeep Prabhakar Chepuri
Regularized Q-learning through Robust Averaging
Peter Schmitt-Förster, Tobias Sutter
Sparsest Models Elude Pruning: An Exposé of Pruning’s Current Capabilities
Stephen Zhang, Vardan Papyan
Efficient Precision and Recall Metrics for Assessing Generative Models using Hubness-aware Sampling
Yuanbang Liang, Jing Wu, Yu-Kun Lai et al.
Reprompting: Automated Chain-of-Thought Prompt Inference Through Gibbs Sampling
Weijia Xu, Andrzej Banburski-Fahey, Nebojsa Jojic
Non-Asymptotic Analysis for Single-Loop (Natural) Actor-Critic with Compatible Function Approximation
Yudan Wang, Yue Wang, Yi Zhou et al.
Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining
Florian Tramer, Gautam Kamath, Nicholas Carlini
Differentially Private Post-Processing for Fair Regression
Ruicheng Xian, Qiaobo Li, Gautam Kamath et al.
An Empirical Study Into What Matters for Calibrating Vision-Language Models
Weijie Tu, Weijian Deng, Dylan Campbell et al.
Position: Automatic Environment Shaping is the Next Frontier in RL
Younghyo Park, Gabriel Margolis, Pulkit Agrawal
LLM Maybe LongLM: SelfExtend LLM Context Window Without Tuning
Hongye Jin, Xiaotian Han, Jingfeng Yang et al.
Evaluating Model Bias Requires Characterizing its Mistakes
Isabela Albuquerque, Jessica Schrouff, David Warde-Farley et al.
Probabilistic Subgoal Representations for Hierarchical Reinforcement Learning
Vivienne Wang, Tinghuai Wang, wenyan yang et al.
LAGMA: LAtent Goal-guided Multi-Agent Reinforcement Learning
Hyungho Na, IL CHUL MOON
How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
Ryan Liu, Theodore R Sumers, Ishita Dasgupta et al.
Image Fusion via Vision-Language Model
Zixiang Zhao, Lilun Deng, Haowen Bai et al.
Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss
Ingvar Ziemann, Stephen Tu, George Pappas et al.
Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models
Raviteja Vemulapalli, Hadi Pouransari, Fartash Faghri et al.
A Computational Framework for Solving Wasserstein Lagrangian Flows
Kirill Neklyudov, Rob Brekelmans, Alexander Tong et al.
Contextual Feature Selection with Conditional Stochastic Gates
Ram Dyuthi Sristi, Ofir Lindenbaum, Shira Lifshitz et al.
Weisfeiler Leman for Euclidean Equivariant Machine Learning
Snir Hordan, Tal Amir, Nadav Dym
Learning to Scale Logits for Temperature-Conditional GFlowNets
Minsu Kim, Joohwan Ko, Taeyoung Yun et al.
Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method
Qinghua Tao, Francesco Tonin, Alex Lambert et al.
Reinforcement Learning and Regret Bounds for Admission Control
Lucas Weber, Ana Busic, Jiamin ZHU
Large Scale Dataset Distillation with Domain Shift
Noel Loo, Alaa Maalouf, Ramin Hasani et al.
OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Models
Ali AhmadiTeshnizi, Wenzhi Gao, Madeleine Udell
Autoformalizing Euclidean Geometry
Logan Murphy, Kaiyu Yang, Jialiang Sun et al.
Efficient Policy Evaluation with Offline Data Informed Behavior Policy Design
Shuze Liu, Shangtong Zhang
QuIP$\#$: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks
Albert Tseng, Jerry Chee, Qingyao Sun et al.
Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis
Stefan Horoi, Albert Manuel Orozco Camacho, Eugene Belilovsky et al.
Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo
Stephen Zhao, Rob Brekelmans, Alireza Makhzani et al.
Revealing Vision-Language Integration in the Brain with Multimodal Networks
Vighnesh Subramaniam, Colin Conwell, Christopher Wang et al.
COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability
Xingang Guo, Fangxu Yu, Huan Zhang et al.
Learning Optimal Projection for Forecast Reconciliation of Hierarchical Time Series
Asterios Tsiourvas, Wei Sun, Georgia Perakis et al.
Saliency strikes back: How filtering out high frequencies improves white-box explanations
Sabine Muzellec, Thomas FEL, Victor Boutin et al.
Switching the Loss Reduces the Cost in Batch Reinforcement Learning
Alex Ayoub, Kaiwen Wang, Vincent Liu et al.
Sampling-based Multi-dimensional Recalibration
Youngseog Chung, Ian Char, Jeff Schneider
NExT: Teaching Large Language Models to Reason about Code Execution
Ansong Ni, Miltiadis Allamanis, Arman Cohan et al.
Hierarchical Novelty Detection via Fine-Grained Evidence Allocation
Spandan Pyakurel, Qi Yu
Executable Code Actions Elicit Better LLM Agents
Xingyao Wang, Yangyi Chen, Lifan Yuan et al.
Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision
Collin Burns, Pavel Izmailov, Jan Kirchner et al.
PANDA: Expanded Width-Aware Message Passing Beyond Rewiring
Jeongwhan Choi, Sumin Parksumin, Hyowon Wi et al.
Towards Efficient Training and Evaluation of Robust Models against $l_0$ Bounded Adversarial Perturbations
Xuyang Zhong, Yixiao HUANG, Chen Liu
Position: AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Research
Riley Simmons-Edler, Ryan Badman, Shayne Longpre et al.
Harnessing Hierarchical Label Distribution Variations in Test Agnostic Long-tail Recognition
Zhiyong Yang, Qianqian Xu, Zitai Wang et al.
MMPareto: Boosting Multimodal Learning with Innocent Unimodal Assistance
Yake Wei, Di Hu
Uniformly Stable Algorithms for Adversarial Training and Beyond
Jiancong Xiao, Jiawei Zhang, Zhi-Quan Luo et al.
Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization
Yihan Du, Anna Winnicki, Gal Dalal et al.
Position: Intent-aligned AI Systems Must Optimize for Agency Preservation
Catalin Mitelut, Benjamin Smith, Peter Vamplew
Model-Based Minimum Bayes Risk Decoding for Text Generation
Yuu Jinnai, Tetsuro Morimura, Ukyo Honda et al.
On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity
Junyi FAN, Yuxuan Han, Zijian Liu et al.
Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models
Tanmay Gautam, Youngsuk Park, Hao Zhou et al.
Collage: Light-Weight Low-Precision Strategy for LLM Training
Tao Yu, Gaurav Gupta, KARTHICK GOPALSWAMY et al.
SelfVC: Voice Conversion With Iterative Refinement using Self Transformations
Paarth Neekhara, Shehzeen Hussain, Rafael Valle et al.
Evaluating Quantized Large Language Models
Shiyao Li, Xuefei Ning, Luning Wang et al.
PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design
Alexandre Duval, Victor Schmidt, Santiago Miret et al.
First-Order Manifold Data Augmentation for Regression Learning
Ilya Kaufman, Omri Azencot
Recurrent Distance Filtering for Graph Representation Learning
Yuhui Ding, Antonio Orvieto, Bobby He et al.
Zero-Shot Unsupervised and Text-Based Audio Editing Using DDPM Inversion
Hila Manor, Tomer Michaeli
Feel-Good Thompson Sampling for Contextual Dueling Bandits
Xuheng Li, Heyang Zhao, Quanquan Gu
Causal Discovery with Fewer Conditional Independence Tests
Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler
What is the Long-Run Distribution of Stochastic Gradient Descent? A Large Deviations Analysis
Waïss Azizian, Franck Iutzeler, Jérôme Malick et al.
Exploiting Human-AI Dependence for Learning to Defer
Zixi Wei, Yuzhou Cao, Lei Feng
Scene Graph Generation Strategy with Co-occurrence Knowledge and Learnable Term Frequency
Hyeongjin Kim, Sangwon Kim, Dasom Ahn et al.
Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph
Yufei Kuang, Jie Wang, Yuyan Zhou et al.
Gradient Compressed Sensing: A Query-Efficient Gradient Estimator for High-Dimensional Zeroth-Order Optimization
Ruizhong Qiu, Hanghang Tong
Fundamental Limitations of Alignment in Large Language Models
Yotam Wolf, Noam Wies, Oshri Avnery et al.
Flexible Residual Binarization for Image Super-Resolution
Yulun Zhang, Haotong Qin, Zixiang Zhao et al.
SFC: Achieve Accurate Fast Convolution under Low-precision Arithmetic
Liulu He, yufei zhao, rui gao et al.
Predicting Dose-Response Curves with Deep Neural Networks
Pedro A. Campana, Paul Prasse, Tobias Scheffer
Provably Efficient Long-Horizon Exploration in Monte Carlo Tree Search through State Occupancy Regularization
Liam Schramm, Abdeslam Boularias
Causal Effect Identification in LiNGAM Models with Latent Confounders
Daniele Tramontano, Yaroslav Kivva, Saber Salehkaleybar et al.
Transformers, parallel computation, and logarithmic depth
Clayton Sanford, Daniel Hsu, Matus Telgarsky
Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions
Jon Vadillo, Roberto Santana, Jose A Lozano
Tilt and Average : Geometric Adjustment of the Last Layer for Recalibration
Gyusang Cho, Chan-Hyun Youn
Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation
Pei Liu, Luping Ji
Sliding Down the Stairs: How Correlated Latent Variables Accelerate Learning with Neural Networks
Lorenzo Bardone, Sebastian Goldt
Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions
Jingtan Wang, Xiaoqiang Lin, Rui Qiao et al.
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning
Dake Zhang, Boxiang Lyu, Shuang Qiu et al.
Rotational Equilibrium: How Weight Decay Balances Learning Across Neural Networks
Atli Kosson, Bettina Messmer, Martin Jaggi
Implicit Representations for Constrained Image Segmentation
Jan Philipp Schneider, Mishal Fatima, Jovita Lukasik et al.
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics
Manuel Brenner, Florian Hess, Georgia Koppe et al.
When is Transfer Learning Possible?
My Phan, Kianté Brantley, Stephanie Milani et al.
Improving Context Understanding in Multimodal Large Language Models via Multimodal Composition Learning
Wei Li, Hehe Fan, Yongkang Wong et al.
Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction
He Zhang, Chang Liu, wang et al.
InferCept: Efficient Intercept Support for Augmented Large Language Model Inference
Reyna Abhyankar, Zijian He, Vikranth Srivatsa et al.
Scalable Safe Policy Improvement for Factored Multi-Agent MDPs
Federico Bianchi, Edoardo Zorzi, Alberto Castellini et al.
Local Feature Selection without Label or Feature Leakage for Interpretable Machine Learning Predictions
Harrie Oosterhuis, Lijun Lyu, Avishek Anand
Generalization Analysis for Multi-Label Learning
Yi-Fan Zhang, Min-Ling Zhang
On the sample complexity of conditional independence testing with Von Mises estimator with application to causal discovery
Fateme Jamshidi, Luca Ganassali, Negar Kiyavash
Coarse-To-Fine Tensor Trains for Compact Visual Representations
Sebastian Loeschcke, Dan Wang, Christian Leth-Espensen et al.
How Smooth Is Attention?
Valérie Castin, Pierre Ablin, Gabriel Peyré
Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits
Kyoungseok Jang, Chicheng Zhang, Kwang-Sung Jun
Lightweight Image Super-Resolution via Flexible Meta Pruning
Yulun Zhang, Kai Zhang, Luc Van Gool et al.
On the Nonlinearity of Layer Normalization
Yunhao Ni, Yuxin Guo, Junlong Jia et al.
KnowFormer: Revisiting Transformers for Knowledge Graph Reasoning
Junnan Liu, Qianren Mao, Weifeng Jiang et al.
Fundamental Limits of Distributed Covariance Matrix Estimation Under Communication Constraints
Mohammad Reza Rahmani, Mohammad Hossein Yassaee, Mohammad Ali Maddah Ali et al.
Sign Rank Limitations for Inner Product Graph Decoders
Su Hyeong Lee, QINGQI ZHANG, Risi Kondor
LoCoCo: Dropping In Convolutions for Long Context Compression
Ruisi Cai, Yuandong Tian, Zhangyang “Atlas” Wang et al.
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases
Zechun Liu, Changsheng Zhao, Forrest Iandola et al.
GenCO: Generating Diverse Designs with Combinatorial Constraints
Aaron Ferber, Arman Zharmagambetov, Taoan Huang et al.
TravelPlanner: A Benchmark for Real-World Planning with Language Agents
Jian Xie, Kai Zhang, Jiangjie Chen et al.
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
Jiawei Zhao, Zhenyu Zhang, Beidi Chen et al.
Dense Reward for Free in Reinforcement Learning from Human Feedback
Alexander Chan, Hao Sun, Samuel Holt et al.
Training-Free Long-Context Scaling of Large Language Models
Chenxin An, Fei Huang, Jun Zhang et al.
MD tree: a model-diagnostic tree grown on loss landscape
Yefan Zhou, Jianlong Chen, Qinxue Cao et al.
ReLU Network with Width $d+\mathcal{O}(1)$ Can Achieve Optimal Approximation Rate
Chenghao Liu, Minghua Chen
Characterizing ResNet's Universal Approximation Capability
Chenghao Liu, Enming Liang, Minghua Chen
Position: Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback
Vincent Conitzer, Rachel Freedman, Jobstq Heitzig et al.
PARDEN, Can You Repeat That? Defending against Jailbreaks via Repetition
Ziyang Zhang, Qizhen Zhang, Jakob Foerster
Minimum Norm Interpolation Meets The Local Theory of Banach Spaces
Gil Kur, Pedro Abdalla, Pierre Bizeul et al.
Individual Fairness in Graph Decomposition
Kamesh Munagala, Govind S. Sankar
SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models
Xiaoxuan Wang, ziniu hu, Pan Lu et al.
Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning
Michael Matthews, Michael Beukman, Benjamin Ellis et al.
Bivariate Causal Discovery using Bayesian Model Selection
Anish Dhir, Samuel Power, Mark van der Wilk
BRAIn: Bayesian Reward-conditioned Amortized Inference for natural language generation from feedback
Gaurav Pandey, Yatin Nandwani, Tahira Naseem et al.
Adaptive Online Experimental Design for Causal Discovery
Muhammad Qasim Elahi, Lai Wei, Murat Kocaoglu et al.
Joint Composite Latent Space Bayesian Optimization
Natalie Maus, Zhiyuan Jerry Lin, Maximilian Balandat et al.
Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents
Chung-En Sun, Sicun Gao, Lily Weng
Spectral Phase Transition and Optimal PCA in Block-Structured Spiked Models
Pierre Mergny, Justin Ko, FLORENT KRZAKALA
A Bayesian Approach to Online Planning
Nir Greshler, David Ben Eli, Carmel Rabinovitz et al.
Theoretical insights for diffusion guidance: A case study for Gaussian mixture models
Yuchen Wu, Minshuo Chen, Zihao Li et al.
Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models
Dennis Wu, Jerry Yao-Chieh Hu, Teng-Yun Hsiao et al.
Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning
Hongming Zhang, Tongzheng Ren, Chenjun Xiao et al.
Position: Video as the New Language for Real-World Decision Making
Sherry Yang, Jacob C Walker, Jack Parker-Holder et al.
Agent Instructs Large Language Models to be General Zero-Shot Reasoners
Nicholas Crispino, Kyle Montgomery, Fankun Zeng et al.
Aligning Transformers with Weisfeiler-Leman
Luis Müller, Christopher Morris
Position: Will we run out of data? Limits of LLM scaling based on human-generated data
Pablo Villalobos, Anson Ho, Jaime Sevilla et al.
Learning Linear Block Error Correction Codes
Yoni Choukroun, Lior Wolf
ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints
Akhil Agnihotri, Rahul Jain, Haipeng Luo
Local vs. Global Interpretability: A Computational Complexity Perspective
Shahaf Bassan, Guy Amir, Guy Katz
A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle
Nadav Hallak, Kfir Levy
Fault Tolerant ML: Efficient Meta-Aggregation and Synchronous Training
Tehila Dahan, Kfir Levy
Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems
Roie Reshef, Kfir Levy
Efficient Value Iteration for s-rectangular Robust Markov Decision Processes
Navdeep Kumar, Kaixin Wang, Kfir Levy et al.
Dynamic Byzantine-Robust Learning: Adapting to Switching Byzantine Workers
Ron Dorfman, Naseem Yehya, Kfir Levy
Retrieval-Augmented Score Distillation for Text-to-3D Generation
Junyoung Seo, Susung Hong, Wooseok Jang et al.
Parameter-Dependent Competitive Analysis for Online Capacitated Coverage Maximization through Boostings and Attenuations
Pan Xu
Promoting External and Internal Equities Under Ex-Ante/Ex-Post Metrics in Online Resource Allocation
Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
Eureka-Moments in Transformers: Multi-Step Tasks Reveal Softmax Induced Optimization Problems
David T. Hoffmann, Simon Schrodi, Jelena Bratulić et al.
Stochastic Q-learning for Large Discrete Action Spaces
Fares Fourati, Vaneet Aggarwal, Mohamed-Slim Alouini
Federated Combinatorial Multi-Agent Multi-Armed Bandits
Fares Fourati, Mohamed-Slim Alouini, Vaneet Aggarwal
In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization
Herilalaina Rakotoarison, Steven Adriaensen, Neeratyoy Mallik et al.
Bayesian Optimization of Function Networks with Partial Evaluations
Poompol Buathong, Jiayue Wan, Raul Astudillo et al.
Autoencoding Conditional Neural Processes for Representation Learning
Victor Prokhorov, Ivan Titov, Siddharth N
BLO-SAM: Bi-level Optimization Based Finetuning of the Segment Anything Model for Overfitting-Preventing Semantic Segmentation
Li Zhang, Youwei Liang, Ruiyi Zhang et al.
A Touch, Vision, and Language Dataset for Multimodal Alignment
Letian Fu, Gaurav Datta, Huang Huang et al.
Prospective Side Information for Latent MDPs
Jeongyeol Kwon, Yonathan Efroni, Shie Mannor et al.
On The Complexity of First-Order Methods in Stochastic Bilevel Optimization
Jeongyeol Kwon, Dohyun Kwon, Hanbaek Lyu
Neural NeRF Compression
Tuan Pham, Stephan Mandt
SimPro: A Simple Probabilistic Framework Towards Realistic Long-Tailed Semi-Supervised Learning
Chaoqun Du, Yizeng Han, Gao Huang
Graph Neural Network Explanations are Fragile
Jiate Li, Meng Pang, Yun Dong et al.
AlphaFold Meets Flow Matching for Generating Protein Ensembles
Bowen Jing, Bonnie Berger, Tommi Jaakkola
Generalization Error of Graph Neural Networks in the Mean-field Regime
Gholamali Aminian, Yixuan He, Gesine Reinert et al.
ConTextual: Evaluating Context-Sensitive Text-Rich Visual Reasoning in Large Multimodal Models
Rohan Wadhawan, Hritik Bansal, Kai-Wei Chang et al.
Explorations of Self-Repair in Language Models
Cody Rushing, Neel Nanda