Most Cited ICML "trajectory information" Papers
5,975 papers found • Page 20 of 30
Conference
SAH-Drive: A Scenario-Aware Hybrid Planner for Closed-Loop Vehicle Trajectory Generation
Yuqi Fan, Zhiyong Cui, Zhenning Li et al.
From Token to Rhythm: A Multi-Scale Approach for ECG-Language Pretraining
Fuying Wang, Jiacheng Xu, Lequan Yu
Efficient Curvature-Aware Hypergradient Approximation for Bilevel Optimization
Youran Dong, Junfeng Yang, Wei Yao et al.
FedBEns: One-Shot Federated Learning based on Bayesian Ensemble
Jacopo Talpini, Marco Savi, Giovanni Neglia
On the Similarities of Embeddings in Contrastive Learning
Chungpa Lee, Sehee Lim, Kibok Lee et al.
SCENT: Robust Spatiotemporal Learning for Continuous Scientific Data via Scalable Conditioned Neural Fields
David K Park, Xihaier Luo, Guang Zhao et al.
Automatic Differentiation of Optimization Algorithms with Time-Varying Updates
Sheheryar Mehmood, Peter Ochs
Layer-wise Quantization for Quantized Optimistic Dual Averaging
Anh Duc Nguyen, Ilia Markov, Zhengqing Wu et al.
Rethinking the Bias of Foundation Model under Long-tailed Distribution
Jiahao Chen, Bin Qin, Jiangmeng Li et al.
Online Learning in Betting Markets: Profit versus Prediction
Haiqing Zhu, Alexander Soen, Yun Kuen Cheung et al.
FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning
Ganyu Wang, Jinjie Fang, Maxwell (Juncheng) Yin et al.
Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
Erica Zhang, Fangzhao Zhang, Mert Pilanci
Concurrent Reinforcement Learning with Aggregated States via Randomized Least Squares Value Iteration
Yan Chen, Jerry Bai, Yiteng Zhang et al.
When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal Abstractions
Zhening Li, Gabriel Poesia, Armando Solar-Lezama
ADIOS: Antibody Development via Opponent Shaping
Sebastian Towers, Aleksandra Kalisz, Philippe Robert et al.
End-to-End Learning Framework for Solving Non-Markovian Optimal Control
Xiaole Zhang, Peiyu Zhang, Xiongye Xiao et al.
On the Role of Edge Dependency in Graph Generative Models
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos et al.
Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth
Kevin Kögler, Aleksandr Shevchenko, Hamed Hassani et al.
Double Momentum Method for Lower-Level Constrained Bilevel Optimization
Wanli Shi, Yi Chang, Bin Gu
Learning State-Based Node Representations from a Class Hierarchy for Fine-Grained Open-Set Detection
Spandan Pyakurel, Qi Yu
Sample Complexity of Correlation Detection in the Gaussian Wigner Model
Dong Huang, Pengkun Yang
Sparse Training from Random Initialization: Aligning Lottery Ticket Masks using Weight Symmetry
Mohammed Adnan, Rohan Jain, Ekansh Sharma et al.
Meta Optimality for Demographic Parity Constrained Regression via Post-Processing
Kazuto Fukuchi
On Exact Bit-level Reversible Transformers Without Changing Architecture
Guoqiang Zhang, John Lewis, W. Bastiaan Kleijn
Anytime-Constrained Equilibria in Polynomial Time
Jeremy McMahan
PEINR: A Physics-enhanced Implicit Neural Representation for High-Fidelity Flow Field Reconstruction
Liming Shen, Liang Deng, Chongke Bi et al.
Learning the Target Network in Function Space
Kavosh Asadi, Yao Liu, Shoham Sabach et al.
FOCoOp: Enhancing Out-of-Distribution Robustness in Federated Prompt Learning for Vision-Language Models
Xinting Liao, Weiming Liu, Jiaming Qian et al.
Suitability Filter: A Statistical Framework for Classifier Evaluation in Real-World Deployment Settings
Angéline Pouget, Mohammad Yaghini, Stephan Rabanser et al.
Position: Towards Implicit Prompt For Text-To-Image Models
Yue Yang, Yuqi Lin, Hong Liu et al.
Breaking the Quadratic Barrier: Robust Cardinality Sketches for Adaptive Queries
Edith Cohen, Mihir Singhal, Uri Stemmer
On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks
Junwei Su, Chuan Wu
Action-Dependent Optimality-Preserving Reward Shaping
Grant Forbes, Jianxun Wang, Leonardo Villalobos-Arias et al.
Constrained Pareto Set Identification with Bandit Feedback
Cyrille Kone, Emilie Kaufmann, Laura Richert
LIDAO: Towards Limited Interventions for Debiasing (Large) Language Models
Tianci Liu, Haoyu Wang, Shiyang Wang et al.
PIPA: Preference Alignment as Prior-Informed Statistical Estimation
Junbo Li, Zhangyang “Atlas” Wang, qiang liu
TeDS: Joint Learning of Diachronic and Synchronic Perspectives in Quaternion Space for Temporal Knowledge Graph Completion
Jiujiang Guo, Mankun Zhao, Wenbin Zhang et al.
Smooth Interpolation for Improved Discrete Graph Generative Models
Yuxuan Song, Juntong Shi, Jingjing Gong et al.
LLM Enhancers for GNNs: An Analysis from the Perspective of Causal Mechanism Identification
Hang Gao, Huang Wenxuan, Fengge Wu et al.
Fusing Reward and Dueling Feedback in Stochastic Bandits
Xuchuang Wang, Qirun Zeng, Jinhang Zuo et al.
Kernel Quantile Embeddings and Associated Probability Metrics
Masha Naslidnyk, Siu Lun Chau, Francois-Xavier Briol et al.
Multiple-policy Evaluation via Density Estimation
Yilei Chen, Aldo Pacchiano, Ioannis Paschalidis
Learning Curves of Stochastic Gradient Descent in Kernel Regression
Haihan Zhang, Weicheng Lin, Yuanshi Liu et al.
Rhomboid Tiling for Geometric Graph Deep Learning
Yipeng Zhang, Longlong Li, Kelin Xia
L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental Learning
Xiang Zhang, Run He, Chen Jiao et al.
Enhancing Certified Robustness via Block Reflector Orthogonal Layers and Logit Annealing Loss
Bo-Han Lai, Pin-Han Huang, Bo-Han Kung et al.
Flow-based Domain Randomization for Learning and Sequencing Robotic Skills
Aidan Curtis, Eric Li, Michael S Noseworthy et al.
HetSSNet: Spatial-Spectral Heterogeneous Graph Learning Network for Panchromatic and Multispectral Images Fusion
Mengting Ma, Yizhen Jiang, Mengjiao Zhao et al.
Zero-Sum Positional Differential Games as a Framework for Robust Reinforcement Learning: Deep Q-Learning Approach
Anton Plaksin, Vitaly Kalev
Information Bottleneck-guided MLPs for Robust Spatial-temporal Forecasting
Min Chen, Guansong Pang, Wenjun Wang et al.
Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors
Shuangpeng Han, Mengmi Zhang
Efficiently Vectorized MCMC on Modern Accelerators
Hugh Dance, Pierre Glaser, Peter Orbanz et al.
High-Dimensional Geometric Streaming for Nearly Low Rank Data
Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni et al.
Hyperbolic-PDE GNN: Spectral Graph Neural Networks in the Perspective of A System of Hyperbolic Partial Differential Equations
Juwei Yue, Haikuo Li, Jiawei Sheng et al.
Perturb-and-Project: Differentially Private Similarities and Marginals
Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto et al.
Curse of High Dimensionality Issue in Transformer for Long Context Modeling
Shuhai Zhang, Zeng You, Yaofo Chen et al.
EmoGrowth: Incremental Multi-label Emotion Decoding with Augmented Emotional Relation Graph
Kaicheng Fu, Changde Du, Jie Peng et al.
Multiaccuracy and Multicalibration via Proxy Groups
Beepul Bharti, Mary Clemens-Sewall, Paul H. Yi et al.
Stochastic Optimization with Arbitrary Recurrent Data Sampling
William Powell, Hanbaek Lyu
Predictive Performance Comparison of Decision Policies Under Confounding
Luke Guerdan, Amanda Coston, Ken Holstein et al.
Learning Likelihood-Free Reference Priors
Nick Bishop, Daniel Jarne Ornia, Joel Dyer et al.
TMetaNet: Topological Meta-Learning Framework for Dynamic Link Prediction
Hao Li, Hao Wan, Yuzhou Chen et al.
Self-Supervised Transformers as Iterative Solution Improvers for Constraint Satisfaction
Yudong W Xu, Wenhao Li, Scott Sanner et al.
Efficient PAC Learnability of Dynamical Systems Over Multilayer Networks
Zirou Qiu, Abhijin Adiga, Madhav Marathe et al.
Generative Modeling Reinvents Supervised Learning: Label Repurposing with Predictive Consistency Learning
Yang Li, Jiale Ma, Yebin Yang et al.
Learning with Exact Invariances in Polynomial Time
Ashkan Soleymani, Behrooz Tahmasebi, Stefanie Jegelka et al.
Statistical Test for Feature Selection Pipelines by Selective Inference
Tomohiro Shiraishi, Tatsuya Matsukawa, Shuichi Nishino et al.
Provable Zero-Shot Generalization in Offline Reinforcement Learning
Zhiyong Wang, Chen Yang, John C. S. Lui et al.
Contextures: Representations from Contexts
Runtian Zhai, Kai Yang, Burak VARICI et al.
MASS: Mathematical Data Selection via Skill Graphs for Pretraining Large Language Models
Jiazheng Li, Lu Yu, Qing Cui et al.
Provable Length Generalization in Sequence Prediction via Spectral Filtering
Annie Marsden, Evan Dogariu, Naman Agarwal et al.
Differentially Private Boxplots
Kelly Ramsay, Jairo Diaz-Rodriguez
Zero-Shot Cyclic Peptide Design via Composable Geometric Constraints
Dapeng Jiang, Xiangzhe Kong, Jiaqi Han et al.
Causal Inference from Competing Treatments
Ana-Andreea Stoica, Vivian Y. Nastl, Moritz Hardt
Latent variable model for high-dimensional point process with structured missingness
Maksim Sinelnikov, Manuel Haussmann, Harri Lähdesmäki
New Bounds for Sparse Variational Gaussian Processes
Michalis Titsias
Closed-form Solutions: A New Perspective on Solving Differential Equations
Shu Wei, Yanjie Li, Lina Yu et al.
Adaptive Sensitivity Analysis for Robust Augmentation against Natural Corruptions in Image Segmentation
Laura Zheng, Wenjie Wei, Tony Wu et al.
Active Learning with Selective Time-Step Acquisition for PDEs
Yegon Kim, Hyunsu Kim, Gyeonghoon Ko et al.
Learning Mean Field Control on Sparse Graphs
Christian Fabian, Kai Cui, Heinz Koeppl
Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Exploration
Andreas Kontogiannis, Konstantinos Papathanasiou, Yi Shen et al.
Inexact Newton-type Methods for Optimisation with Nonnegativity Constraints
Oscar Smee, Fred Roosta
Mastering Zero-Shot Interactions in Cooperative and Competitive Simultaneous Games
Yannik Mahlau, Frederik Schubert, Bodo Rosenhahn
Enforcing Idempotency in Neural Networks
Nikolaj Jensen, Jamie Vicary
Understanding the Kronecker Matrix-Vector Complexity of Linear Algebra
Raphael Meyer, William Swartworth, David Woodruff
Mechanistic PDE Networks for Discovery of Governing Equations
Adeel Pervez, Efstratios Gavves, Francesco Locatello
Trust-Region Twisted Policy Improvement
Joery de Vries, Jinke He, Yaniv Oren et al.
Improving Compositional Generation with Diffusion Models Using Lift Scores
Chenning Yu, Sicun Gao
Efficient Motion Prompt Learning for Robust Visual Tracking
Jie Zhao, Xin Chen, Yongsheng Yuan et al.
Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models
Konstantin Donhauser, Kristina Ulicna, Gemma Moran et al.
Configurable Mirror Descent: Towards a Unification of Decision Making
Pengdeng Li, Shuxin Li, Chang Yang et al.
Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations
Davide Sartor, Alberto Sinigaglia, Gian Antonio Susto
Primphormer: Efficient Graph Transformers with Primal Representations
Mingzhen He, Ruikai Yang, Hanling Tian et al.
Sharp Generalization for Nonparametric Regression by Over-Parameterized Neural Networks: A Distribution-Free Analysis in Spherical Covariate
Yingzhen Yang
unMORE: Unsupervised Multi-Object Segmentation via Center-Boundary Reasoning
Yafei YANG, Zihui Zhang, Bo Yang
Open-Domain Text Evaluation via Contrastive Distribution Methods
Sidi Lu, Hongyi Liu, Asli Celikyilmaz et al.
DiNADO: Norm-Disentangled Neurally-Decomposed Oracles for Controlling Language Models
Sidi Lu, Wenbo Zhao, Chenyang Tao et al.
PoisonBench: Assessing Language Model Vulnerability to Poisoned Preference Data
Tingchen Fu, Mrinank Sharma, Phil Torr et al.
Visual Graph Arena: Evaluating Visual Conceptualization of Vision and Multimodal Large Language Models
Zahra Babaiee, Peyman M. Kiasari, Daniela Rus et al.
Subgroups Matter for Robust Bias Mitigation
Anissa Alloula, Charles Jones, Ben Glocker et al.
DRAG: Data Reconstruction Attack using Guided Diffusion
Wa-Kin Lei, Jun-Cheng Chen, Shang-Tse Chen
Improving the Effective Receptive Field of Message-Passing Neural Networks
Shahaf E. Finder, Ron Shapira Weber, Moshe Eliasof et al.
Measuring Stochastic Data Complexity with Boltzmann Influence Functions
Nathan Ng, Roger Grosse, Marzyeh Ghassemi
Sobolev Space Regularised Pre Density Models
Mark Kozdoba, Binyamin Perets, Shie Mannor
Identifying Causal Direction via Variational Bayesian Compression
Quang-Duy Tran, Bao Duong, Phuoc Nguyen et al.
Causal Abstraction Inference under Lossy Representations
Kevin Xia, Elias Bareinboim
SCISSOR: Mitigating Semantic Bias through Cluster-Aware Siamese Networks for Robust Classification
Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
Streamline Without Sacrifice - Squeeze out Computation Redundancy in LMM
Penghao Wu, Lewei Lu, Ziwei Liu
Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach
Zixiao Wang, AmirEmad Ghassami, Ilya Shpitser
Ai-sampler: Adversarial Learning of Markov kernels with involutive maps
Evgenii Egorov, Riccardo Valperga, Efstratios Gavves
Reinforcement Learning with Segment Feedback
Yihan Du, Anna Winnicki, Gal Dalal et al.
Private Truly-Everlasting Robust-Prediction
Uri Stemmer
AutoAL: Automated Active Learning with Differentiable Query Strategy Search
Yifeng Wang, Xueying Zhan, Siyu Huang
Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting
Jan Schuchardt, Mina Dalirrooyfard, Jed Guzelkabaagac et al.
Generalization Bounds via Meta-Learned Model Representations: PAC-Bayes and Sample Compression Hypernetworks
Benjamin Leblanc, Mathieu Bazinet, Nathaniel D'Amours et al.
Neural Collapse Beyond the Unconstrained Features Model: Landscape, Dynamics, and Generalization in the Mean-Field Regime
Diyuan Wu, Marco Mondelli
Improved Last-Iterate Convergence of Shuffling Gradient Methods for Nonsmooth Convex Optimization
Zijian Liu, Zhengyuan Zhou
BECAME: Bayesian Continual Learning with Adaptive Model Merging
Mei Li, Yuxiang Lu, Qinyan Dai et al.
NBDI: A Simple and Effective Termination Condition for Skill Extraction from Task-Agnostic Demonstrations
Myunsoo Kim, Hayeong Lee, Seong-Woong Shim et al.
Provable Interactive Learning with Hindsight Instruction Feedback
Dipendra Misra, Aldo Pacchiano, Robert Schapire
Privacy Preserving Adaptive Experiment Design
Jiachun Li, Kaining Shi, David Simchi-Levi
An Efficient Private GPT Never Autoregressively Decodes
Zhengyi Li, Yue Guan, Kang Yang et al.
Multi-Objective Causal Bayesian Optimization
Shriya Bhatija, Paul-David Zuercher, Jakob Thumm et al.
Evolving Prompts In-Context: An Open-ended, Self-replicating Perspective
Jianyu Wang, Zhiqiang Hu, Lidong Bing
You Always Recognize Me (YARM): Robust Texture Synthesis Against Multi-View Corruption
Weihang Ran, Wei Yuan, Yinqiang Zheng
Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials
Jonathan Scott, Aine E Cahill
Learning from True-False Labels via Multi-modal Prompt Retrieving
Zhongnian Li, Jinghao Xu, Peng Ying et al.
RollingQ: Reviving the Cooperation Dynamics in Multimodal Transformer
Haotian Ni, Yake Wei, Hang Liu et al.
On the Out-of-Distribution Generalization of Self-Supervised Learning
Wenwen Qiang, Jingyao Wang, Zeen Song et al.
Concept-Based Unsupervised Domain Adaptation
Xinyue Xu, Yueying Hu, Hui Tang et al.
An Optimistic Algorithm for online CMDPS with Anytime Adversarial Constraints
Jiahui Zhu, Kihyun Yu, Dabeen Lee et al.
ATraDiff: Accelerating Online Reinforcement Learning with Imaginary Trajectories
Qianlan Yang, Yu-Xiong Wang
UnHiPPO: Uncertainty-aware Initialization for State Space Models
Marten Lienen, Abdullah Saydemir, Stephan Günnemann
Graph Neural Networks with a Distribution of Parametrized Graphs
See Hian Lee, Feng Ji, Kelin Xia et al.
Self-Organizing Visual Prototypes for Non-Parametric Representation Learning
Thalles Silva, Helio Pedrini, Adín Ramírez Rivera
Compositional Curvature Bounds for Deep Neural Networks
Taha Entesari, Sina Sharifi, Mahyar Fazlyab
A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks
Nicholas Monath, Will Grathwohl, Michael Boratko et al.
Refined generalization analysis of the Deep Ritz Method and Physics-Informed Neural Networks
Xianliang Xu, Ye Li, Zhongyi Huang
An Efficient Matrix Multiplication Algorithm for Accelerating Inference in Binary and Ternary Neural Networks
Mohsen Dehghankar, Mahdi Erfanian, Abolfazl Asudeh
Leveraging Predictive Equivalence in Decision Trees
Hayden McTavish, Zachery Boner, Jon Donnelly et al.
Learning Invariant Causal Mechanism from Vision-Language Models
Zeen Song, Siyu Zhao, Xingyu Zhang et al.
Improved Bounds for Pure Private Agnostic Learning: Item-Level and User-Level Privacy
Bo Li, Wei Wang, Peng Ye
Triple Changes Estimator for Targeted Policies
Sina Akbari, Negar Kiyavash
IM-Unpack: Training and Inference with Arbitrarily Low Precision Integers
Zhanpeng Zeng, Karthikeyan Sankaralingam, Vikas Singh
KinDEL: DNA-Encoded Library Dataset for Kinase Inhibitors
Benson Chen, Tomasz Danel, Gabriel Dreiman et al.
Sparse Causal Discovery with Generative Intervention for Unsupervised Graph Domain Adaptation
Junyu Luo, Yuhao Tang, Yiwei Fu et al.
MGit: A Model Versioning and Management System
Wei Hao, Daniel Mendoza, Rafael Mendes et al.
Distribution-aware Fairness Learning in Medical Image Segmentation From A Control-Theoretic Perspective
Yujin Oh, Pengfei Jin, Sangjoon Park et al.
Sampling Binary Data by Denoising through Score Functions
Francis Bach, Saeed Saremi
Position: AI Safety Must Embrace an Antifragile Perspective
Ming Jin, Hyunin Lee
RISE: Radius of Influence based Subgraph Extraction for 3D Molecular Graph Explanation
Jingxiang Qu, Wenhan Gao, Jiaxing Zhang et al.
Learning Survival Distributions with the Asymmetric Laplace Distribution
Deming Sheng, Ricardo Henao
Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation
Michal Lukasik, Lin Chen, Harikrishna Narasimhan et al.
A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints
Michael Munn, Susan Wei
Fast, Accurate Manifold Denoising by Tunneling Riemannian Optimization
Shiyu Wang, Mariam Avagyan, Yihan Shen et al.
Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination
Ilias Diakonikolas, Giannis Iakovidis, Daniel Kane et al.
COMRECGC: Global Graph Counterfactual Explainer through Common Recourse
Gregoire Fournier, Sourav Medya
Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift
Nguyen Nhat Minh To, Paul Wilson, Viet Nguyen et al.
High Dynamic Range Novel View Synthesis with Single Exposure
Kaixuan Zhang, HuWang, Minxian Li et al.
From Feature Interaction to Feature Generation: A Generative Paradigm of CTR Prediction Models
MINGJIA YIN, Junwei Pan, Hao Wang et al.
Collaborative Learning with Different Labeling Functions
yuyang deng, Mingda Qiao
Zero-Inflated Bandits
Haoyu Wei, Runzhe Wan, Lei Shi et al.
Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning
Sunwoo Lee, Jaebak Hwang, Yonghyeon Jo et al.
ADDQ: Adaptive distributional double Q-learning
Leif Döring, Benedikt Wille, Maximilian Birr et al.
Optimal Decision Tree Pruning Revisited: Algorithms and Complexity
Juha Harviainen, Frank Sommer, Manuel Sorge et al.
Efficient Fine-Grained Guidance for Diffusion Model Based Symbolic Music Generation
Tingyu Zhu, Haoyu Liu, Ziyu Wang et al.
The Batch Complexity of Bandit Pure Exploration
Adrienne Tuynman, Rémy Degenne
Position: Certified Robustness Does Not (Yet) Imply Model Security
Andrew C. Cullen, Paul MONTAGUE, Sarah Erfani et al.
IW-GAE: Importance weighted group accuracy estimation for improved calibration and model selection in unsupervised domain adaptation
Taejong Joo, Diego Klabjan
Human-Aligned Image Models Improve Visual Decoding from the Brain
Nona Rajabi, Antonio Ribeiro, Miguel Vasco et al.
MixBridge: Heterogeneous Image-to-Image Backdoor Attack through Mixture of Schrödinger Bridges
Shixi Qin, Zhiyong Yang, Shilong Bao et al.
Discovering Physics Laws of Dynamical Systems via Invariant Function Learning
Shurui Gui, Xiner Li, Shuiwang Ji
Fraud-Proof Revenue Division on Subscription Platforms
Abheek Ghosh, Tzeh Yuan Neoh, Nicholas Teh et al.
Centralized Selection with Preferences in the Presence of Biases
L. Elisa Celis, Amit Kumar, Nisheeth K. Vishnoi et al.
Consensus Based Stochastic Optimal Control
Liyao Lyu, Jingrun Chen
Learning Utilities from Demonstrations in Markov Decision Processes
Filippo Lazzati, Alberto Maria Metelli
Optimally Improving Cooperative Learning in a Social Setting
Shahrzad Haddadan, Cheng Xin, Jie Gao
Reinforcement Learning and Regret Bounds for Admission Control
Lucas Weber, Ana Busic, Jiamin ZHU
Position: Do Not Explain Vision Models Without Context
Paulina Tomaszewska, Przemyslaw Biecek
IMTS is Worth Time $\times$ Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series Prediction
Zhangyi Hu, Jiemin Wu, Hua XU et al.
DeepCrossAttention: Supercharging Transformer Residual Connections
Mike Heddes, Adel Javanmard, Kyriakos Axiotis et al.
Uncertainty-Based Extensible Codebook for Discrete Federated Learning in Heterogeneous Data Silos
Tianyi Zhang, Yu Cao, Dianbo Liu
Random matrix theory improved Fréchet mean of symmetric positive definite matrices
Florent Bouchard, Ammar Mian, Malik TIOMOKO et al.
Unsupervised Episode Generation for Graph Meta-learning
Jihyeong Jung, Sangwoo Seo, Sungwon Kim et al.
Leveraging Offline Data in Linear Latent Contextual Bandits
Chinmaya Kausik, Kevin Tan, Ambuj Tewari
Testing the Limits of Fine-Tuning for Improving Visual Cognition in Vision Language Models
Luca M. Schulze Buschoff, Konstantinos Voudouris, Elif Akata et al.
Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders
Rogelio A. Mancisidor, Robert Jenssen, Shujian Yu et al.
Mask-Enhanced Autoregressive Prediction: Pay Less Attention to Learn More
Xialie Zhuang, Zhikai Jia, Jianjin Li et al.
Does One-shot Give the Best Shot? Mitigating Model Inconsistency in One-shot Federated Learning
Hui Zeng, Wenke Huang, Tongqing Zhou et al.
Prompt-based Visual Alignment for Zero-shot Policy Transfer
Haihan Gao, Rui Zhang, Qi Yi et al.
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards
Chenlu Ye, Yujia Jin, Alekh Agarwal et al.
Matroid Semi-Bandits in Sublinear Time
Ruo-Chun Tzeng, Naoto Ohsaka, Kaito Ariu
Global Context-aware Representation Learning for Spatially Resolved Transcriptomics
Yunhak Oh, Junseok Lee, Yeongmin Kim et al.
Stochastic Layer-Wise Shuffle for Improving Vision Mamba Training
Zizheng Huang, Haoxing Chen, Jiaqi Li et al.
Transformer-Based Spatial-Temporal Counterfactual Outcomes Estimation
He Li, Haoang Chi, Mingyu Liu et al.
BackSlash: Rate Constrained Optimized Training of Large Language Models
Jun Wu, jiangtao wen, Yuxing Han
Time to Spike? Understanding the Representational Power of Spiking Neural Networks in Discrete Time
Duc Anh Nguyen, Ernesto Araya, Adalbert Fono et al.
Quantum Speedup for Hypergraph Sparsification
Chenghua Liu, Minbo Gao, Zhengfeng Ji et al.
Improved Discretization Complexity Analysis of Consistency Models: Variance Exploding Forward Process and Decay Discretization Scheme
Ruofeng Yang, Bo Jiang, Cheng Chen et al.
Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning Framework
Terje Mildner, Oliver Hamelijnck, Paris Giampouras et al.