Most Cited ICML "global interactions" Papers
5,975 papers found • Page 24 of 30
Conference
Fully Dynamic Embedding into $\ell_p$ Spaces
Kiarash Banihashem, Xiang Chen, MohammadTaghi Hajiaghayi et al.
Stay Hungry, Keep Learning: Sustainable Plasticity for Deep Reinforcement Learning
Huaicheng Zhou, Zifeng Zhuang, Donglin Wang
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.
PTTA: Purifying Malicious Samples for Test-Time Model Adaptation
Jing Ma, Hanlin Li, Xiang Xiang
iDPA: Instance Decoupled Prompt Attention for Incremental Medical Object Detection
Huahui Yi, Wei Xu, Ziyuan Qin et al.
ELoRA: Low-Rank Adaptation for Equivariant GNNs
Chen Wang, Siyu Hu, Guangming Tan et al.
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.
ExtPose: Robust and Coherent Pose Estimation by Extending ViTs
Glory Rongyu CHEN, Li'an Zhuo, Linlin Yang et al.
Q-Supervised Contrastive Representation: A State Decoupling Framework for Safe Offline Reinforcement Learning
Zhihe Yang, Yunjian Xu, Yang Zhang
Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining
Florian Tramer, Gautam Kamath, Nicholas Carlini
Weakly Supervised Anomaly Detection via Dual-Tailed Kernel
Walid Durani, Tobias Nitzl, Claudia Plant et al.
Learning Joint Interventional Effects from Single-Variable Interventions in Additive Models
Armin Kekić, Sergio Hernan Garrido Mejia, Bernhard Schölkopf
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.
Boosting Adversarial Robustness with CLAT: Criticality Leveraged Adversarial Training
Bhavna Gopal, Huanrui Yang, Jingyang Zhang et al.
On Mitigating Affinity Bias through Bandits with Evolving Biased Feedback
Matthew Faw, Constantine Caramanis, Jessica Hoffmann
Strengthen Out-of-Distribution Detection Capability with Progressive Self-Knowledge Distillation
Yang Yang, Haonan Xu
Extracting Rare Dependence Patterns via Adaptive Sample Reweighting
Yiqing Li, Yewei Xia, Xiaofei Wang et al.
TransPL: VQ-Code Transition Matrices for Pseudo-Labeling of Time Series Unsupervised Domain Adaptation
Jaeho Kim, Seulki Lee
Ensemble Learned Bloom Filters: Two Oracles are Better than One
Ming Lin, Lin CHEN
ML$^2$-GCL: Manifold Learning Inspired Lightweight Graph Contrastive Learning
Jianqing Liang, Zhiqiang Li, Xinkai Wei et al.
Power Mean Estimation in Stochastic Continuous Monte-Carlo Tree Search
Tuan Dam
Large Scale Dataset Distillation with Domain Shift
Noel Loo, Alaa Maalouf, Ramin Hasani et al.
SecEmb: Sparsity-Aware Secure Federated Learning of On-Device Recommender System with Large Embedding
Peihua Mai, Youlong Ding, Ziyan Lyu et al.
Counterfactual Effect Decomposition in Multi-Agent Sequential Decision Making
Stelios Triantafyllou, Aleksa Sukovic, Yasaman Zolfimoselo et al.
Behavior-agnostic Task Inference for Robust Offline In-context Reinforcement Learning
Long Ma, Fangwei Zhong, Yizhou Wang
Learning Optimal Projection for Forecast Reconciliation of Hierarchical Time Series
Asterios Tsiourvas, Wei Sun, Georgia Perakis 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
Provably Efficient Algorithm for Best Scoring Rule Identification in Online Principal-Agent Information Acquisition
Zichen Wang, Chuanhao Li, Huazheng Wang
Hierarchical Novelty Detection via Fine-Grained Evidence Allocation
Spandan Pyakurel, Qi Yu
HGOT: Self-supervised Heterogeneous Graph Neural Network with Optimal Transport
Yanbei Liu, Chongxu Wang, Zhitao Xiao 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.
Continuously Updating Digital Twins using Large Language Models
Harry Amad, Nicolás Astorga, Mihaela van der Schaar
Three-Dimensional Trajectory Prediction with 3DMoTraj Dataset
Hao Zhou, Xu Yang, Mingyu Fan et al.
Domain-Adapted Diffusion Model for PROTAC Linker Design Through the Lens of Density Ratio in Chemical Space
Zixing Song, Ziqiao Meng, Jose Miguel Hernandez-Lobato
Position: Intent-aligned AI Systems Must Optimize for Agency Preservation
Catalin Mitelut, Benjamin Smith, Peter Vamplew
Better to Teach than to Give: Domain Generalized Semantic Segmentation via Agent Queries with Diffusion Model Guidance
Fan Li, Xuan Wang, Min Qi et al.
On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity
Junyi FAN, Yuxuan Han, Zijian Liu et al.
Revisiting Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model
Kaito Ariu, Alexandre Proutiere, Se-Young Yun
How to Evaluate and Mitigate IP Infringement in Visual Generative AI?
Zhenting Wang, Chen Chen, Vikash Sehwag et al.
A Closer Look at Transformers for Time Series Forecasting: Understanding Why They Work and Where They Struggle
Yu Chen, Nathalia Céspedes, Payam Barnaghi
What Limits Bidirectional Model's Generative Capabilities? A Uni-Bi-Directional Mixture-of-Expert Method For Bidirectional Fine-tuning
Zuchao Li, Yonghua Hei, Qiwei Li et al.
LIMEFLDL: A Local Interpretable Model-Agnostic Explanations Approach for Label Distribution Learning
Xiuyi Jia, Jinchi Li, Yunan Lu et al.
Explicit Discovery of Nonlinear Symmetries from Dynamic Data
Lexiang Hu, Yikang Li, Zhouchen Lin
Training High Performance Spiking Neural Network by Temporal Model Calibration
Jiaqi Yan, Changping Wang, De Ma et al.
Best of Both Worlds: Regret Minimization versus Minimax Play
Adrian Müller, Jon Schneider, EFSTRATIOS PANTELEIMON SKOULAKIS et al.
Exploiting Human-AI Dependence for Learning to Defer
Zixi Wei, Yuzhou Cao, Lei Feng
Differential Privacy Guarantees of Markov Chain Monte Carlo Algorithms
Andrea Bertazzi, Tim Johnston, Gareth Roberts et al.
Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph
Yufei Kuang, Jie Wang, Yuyan Zhou et al.
SDMG: Smoothing Your Diffusion Models for Powerful Graph Representation Learning
Junyou Zhu, Langzhou He, Chao Gao et al.
Branches: Efficiently Seeking Optimal Sparse Decision Trees via AO*
Ayman Chaouki, Jesse Read, Albert Bifet
Flexible Residual Binarization for Image Super-Resolution
Yulun Zhang, Haotong Qin, Zixiang Zhao et al.
Online Robust Reinforcement Learning Through Monte-Carlo Planning
Tuan Dam, Kishan Panaganti, Brahim Driss et al.
Predicting Dose-Response Curves with Deep Neural Networks
Pedro A. Campana, Paul Prasse, Tobias Scheffer
Directed Graph Grammars for Sequence-based Learning
Michael Sun, Orion Foo, Gang Liu et al.
Tilt and Average : Geometric Adjustment of the Last Layer for Recalibration
Gyusang Cho, Chan-Hyun Youn
Private Lossless Multiple Release
Joel Daniel Andersson, Lukas Retschmeier, Boel Nelson et al.
WILTing Trees: Interpreting the Distance Between MPNN Embeddings
Masahiro Negishi, Thomas Gärtner, Pascal Welke
LBI-FL: Low-Bit Integerized Federated Learning with Temporally Dynamic Bit-Width Allocation
Li Ding, Hao Zhang, Wenrui Dai et al.
CAN: Leveraging Clients As Navigators for Generative Replay in Federated Continual Learning
Xuankun Rong, Jianshu Zhang, Kun He et al.
Implicit Representations for Constrained Image Segmentation
Jan Philipp Schneider, Mishal Fatima, Jovita Lukasik et al.
Code-Generated Graph Representations Using Multiple LLM Agents for Material Properties Prediction
Jiao Huang, Qianli Xing, Jinglong Ji 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.
Scalable Safe Policy Improvement for Factored Multi-Agent MDPs
Federico Bianchi, Edoardo Zorzi, Alberto Castellini et al.
Generalization Analysis for Multi-Label Learning
Yi-Fan Zhang, Min-Ling Zhang
FicGCN: Unveiling the Homomorphic Encryption Efficiency from Irregular Graph Convolutional Networks
Zhaoxuan Kan, Husheng Han, shangyi shi et al.
Functional Alignment Can Mislead: Examining Model Stitching
Damian Smith, Harvey Mannering, Antonia Marcu
Lightweight Image Super-Resolution via Flexible Meta Pruning
Yulun Zhang, Kai Zhang, Luc Van Gool et al.
AEQA-NAT : Adaptive End-to-end Quantization Alignment Training Framework for Non-autoregressive Machine Translation
Xiangyu Qu, Guojing Liu, Liang Li
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
An Online Learning Approach to Prompt-based Selection of Generative Models and LLMs
Xiaoyan Hu, Ho-fung Leung, Farzan Farnia
An Improved Clique-Picking Algorithm for Counting Markov Equivalent DAGs via Super Cliques Transfer
Lifu Liu, Shiyuan He, Jianhua Guo
Invariant Deep Uplift Modeling for Incentive Assignment in Online Marketing via Probability of Necessity and Sufficiency
Zexu Sun, Qiyu Han, Hao Yang et al.
Tensorized Multi-View Multi-Label Classification via Laplace Tensor Rank
Qiyu Zhong, Yi Shan, Haobo Wang et al.
Diffusion Models are Secretly Exchangeable: Parallelizing DDPMs via Auto Speculation
Hengyuan Hu, Aniket Das, Dorsa Sadigh et al.
Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning
Yiran Wang, Chenshu Liu, Yunfan Li 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.
Identifying Neural Dynamics Using Interventional State Space Models
Amin Nejatbakhsh, Yixin Wang
Minimum Norm Interpolation Meets The Local Theory of Banach Spaces
Gil Kur, Pedro Abdalla, Pierre Bizeul et al.
EFDTR: Learnable Elliptical Fourier Descriptor Transformer for Instance Segmentation
Jiawei Cao, Chaochen Gu, Hao Cheng et al.
Rethink GraphODE Generalization within Coupled Dynamical System
Guancheng Wan, Zijie Huang, Wanjia Zhao et al.
Causal Logistic Bandits with Counterfactual Fairness Constraints
Jiajun Chen, Jin Tian, Chris Quinn
Hierarchical Reinforcement Learning with Targeted Causal Interventions
Mohammadsadegh Khorasani, Saber Salehkaleybar, Negar Kiyavash et al.
Larger or Smaller Reward Margins to Select Preferences for LLM Alignment?
Kexin Huang, Junkang Wu, Ziqian Chen et al.
Near Optimal Non-asymptotic Sample Complexity of 1-Identification
Zitian Li, Wang Chi Cheung
Rethinking Point Cloud Data Augmentation: Topologically Consistent Deformation
Jian Bi, Qianliang Wu, Xiang Li et al.
Position: Video as the New Language for Real-World Decision Making
Sherry Yang, Jacob C Walker, Jack Parker-Holder et al.
Position: Will we run out of data? Limits of LLM scaling based on human-generated data
Pablo Villalobos, Anson Ho, Jaime Sevilla et al.
Empowering World Models with Reflection for Embodied Video Prediction
Xiaowei Chi, Chun-Kai Fan, Hengyuan Zhang et al.
A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle
Nadav Hallak, Kfir Levy
Efficient Value Iteration for s-rectangular Robust Markov Decision Processes
Navdeep Kumar, Kaixin Wang, Kfir Levy 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
Fast and Provable Algorithms for Sparse PCA with Improved Sample Complexity
Jian-Feng Cai, Zhuozhi XIAN, Jiaxi Ying
Preconditioned Riemannian Gradient Descent Algorithm for Low-Multilinear-Rank Tensor Completion
Yuanwei Zhang, Fengmiao Bian, Xiaoqun Zhang et al.
Efficient Heterogeneity-Aware Federated Active Data Selection
Yingpeng Tang, Chao Ren, Xiaoli Tang 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.
Causality Inspired Federated Learning for OOD Generalization
Jiayuan Zhang, Xuefeng Liu, Jianwei Niu et al.
Revisiting Convergence: Shuffling Complexity Beyond Lipschitz Smoothness
Qi He, Peiran Yu, Ziyi Chen et al.
Divide and Conquer: Grounding LLMs as Efficient Decision-Making Agents via Offline Hierarchical Reinforcement Learning
Zican Hu, Wei Liu, Xiaoye Qu et al.
Enhancing Visual Localization with Cross-Domain Image Generation
Yuanze Wang, Yichao Yan, Shiming Song et al.
Beyond Self-Interest: How Group Strategies Reshape Content Creation in Recommendation Platforms?
Yaolong Yu, Fan Yao, Sinno Jialin Pan
DiffAdvMAP: Flexible Diffusion-Based Framework for Generating Natural Unrestricted Adversarial Examples
Zhengzhao Pan, Hua Chen, Xiaogang Zhang
Simple Randomized Rounding for Max-Min Eigenvalue Augmentation
Jourdain Lamperski, Haeseong Yang, Oleg Prokopyev
Effective Federated Graph Matching
Yang Zhou, Zijie Zhang, Zeru Zhang et al.
Self-cognitive Denoising in the Presence of Multiple Noisy Label Sources
Yi-Xuan Sun, Ya-Lin Zhang, BIN HAN et al.
Federated Continual Learning via Prompt-based Dual Knowledge Transfer
Hongming Piao, Yichen WU, Dapeng Wu et al.
Active Treatment Effect Estimation via Limited Samples
Zhiheng Zhang, Haoxiang Wang, Haoxuan Li et al.
Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning
Qi Xu, Junyang Zhu, Dongdong Zhou et al.
All-Purpose Mean Estimation over R: Optimal Sub-Gaussianity with Outlier Robustness and Low Moments Performance
Jasper Lee, Walter McKelvie, Maoyuan Song et al.
Exactly Tight Information-theoretic Generalization Bounds via Binary Jensen-Shannon Divergence
Yuxin Dong, Haoran Guo, Tieliang Gong et al.
"Why Is There a Tumor?": Tell Me the Reason, Show Me the Evidence
Mengmeng Ma, Tang Li, Yunxiang Peng et al.
Easing Concept Bleeding in Diffusion via Entity Localization and Anchoring
Jiewei Zhang, Song Guo, Peiran Dong et al.
Securing Equal Share: A Principled Approach for Learning Multiplayer Symmetric Games
Jiawei Ge, Yuanhao Wang, Wenzhe Li et al.
Large Displacement Motion Transfer with Unsupervised Anytime Interpolation
Guixiang Wang, Jianjun Li
Bayesian Weight Enhancement with Steady-State Adaptation for Test-time Adaptation in Dynamic Environments
Jae-Hong Lee
Improving Neural Logic Machines via Failure Reflection
Zhiming Li, Yushi Cao, Yan Zheng et al.
Less is More: on the Over-Globalizing Problem in Graph Transformers
Yujie Xing, Xiao Wang, Yibo Li et al.
Improved and Oracle-Efficient Online $\ell_1$-Multicalibration
Rohan Ghuge, Vidya Muthukumar, Sahil Singla
Energy-Efficient Gaussian Processes Using Low-Precision Arithmetic
Nicolas Alder, Ralf Herbrich
Learning Attribute-Aware Hash Codes for Fine-Grained Image Retrieval via Query Optimization
Peng Wang, Yong Li, Lin Zhao et al.
Mol-AE: Auto-Encoder Based Molecular Representation Learning With 3D Cloze Test Objective
Junwei Yang, Kangjie Zheng, Siyu Long et al.
The Ripple Effect: On Unforeseen Complications of Backdoor Attacks
Rui Zhang, Yun Shen, Hongwei Li et al.
Efficient Federated Incomplete Multi-View Clustering
Suyuan Liu, Hao Yu, Hao Tan et al.
Faster Stochastic Optimization with Arbitrary Delays via Adaptive Asynchronous Mini-Batching
Amit Attia, Ofir Gaash, Tomer Koren
Towards Resource-friendly, Extensible and Stable Incomplete Multi-view Clustering
Shengju Yu, Dong Zhibin, Siwei Wang et al.
Noisy SIGNSGD Is More Differentially Private Than You (Might) Think
Richeng Jin, Huaiyu (David) Dai
Scalable Multiple Kernel Clustering: Learning Clustering Structure from Expectation
Weixuan Liang, En Zhu, Shengju Yu et al.
Decouple then Classify: A Dynamic Multi-view Labeling Strategy with Shared and Specific Information
Xinhang Wan, Jiyuan Liu, Xinwang Liu et al.
Ad Hoc Teamwork via Offline Goal-Based Decision Transformers
Xinzhi Zhang, Hoehi Chan, Deheng Ye et al.
Efficient Source-free Unlearning via Energy-Guided Data Synthesis and Discrimination-Aware Multitask Optimization
Xiuyuan Wang, Chaochao Chen, Weiming Liu et al.
Discovering a Zero (Zero-Vector Class of Machine Learning)
Harikrishna Metta, Venkatesh Babu Radhakrishnan
Sparse Video-Gen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity
Haocheng Xi, Shuo Yang, Yilong Zhao et al.
FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees
Jiahao Liu, Yipeng Zhou, Di Wu et al.
High-Dimensional Tensor Regression With Oracle Properties
Wenbin Wang, Yu Shi, Ziping Zhao
Attack-free Evaluating and Enhancing Adversarial Robustness on Categorical Data
Yujun Zhou, Yufei Han, Haomin Zhuang et al.
Bridging Environments and Language with Rendering Functions and Vision-Language Models
Théo Cachet, Christopher Dance, Olivier Sigaud
A-PSRO: A Unified Strategy Learning Method with Advantage Metric for Normal-form Games
Yudong Hu, Haoran Li, Congying Han et al.
Convergence of Mean-Field Langevin Stochastic Descent-Ascent for Distributional Minimax Optimization
Zhangyi Liu, Feng Liu, Rui Gao et al.
Fine-grained Local Sensitivity Analysis of Standard Dot-Product Self-Attention
Aaron Havens, Alexandre Araujo, Huan Zhang et al.
Beyond Communication Overhead: A Multilevel Monte Carlo Approach for Mitigating Compression Bias in Distributed Learning
Ze'ev Zukerman, Bassel Hamoud, Kfir Levy
BaWA: Automatic Optimizing Pruning Metric for Large Language Models with Balanced Weight and Activation
Lian Liu, Xiandong Zhao, Guanchen Li et al.
Latent Variable Estimation in Bayesian Black-Litterman Models
Thomas Y.L. Lin, Jerry Yao-Chieh Hu, Wan-Jiun Paul Chiou et al.
Improved Lower Bounds for First-order Stochastic Non-convex Optimization under Markov Sampling
Zhenyu Sun, Ermin Wei
SEAD: Unsupervised Ensemble of Streaming Anomaly Detectors
Saumya Gaurang Shah, Abishek Sankararaman, Balakrishnan Narayanaswamy et al.
Understanding the Unfairness in Network Quantization
Bing Liu, wenjun Miao, Boyu Zhang et al.
Adversarial Robustness via Deformable Convolution with Stochasticity
Yanxiang Ma, Zixuan Huang, Minjing Dong et al.
Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection
Louis Béthune, David Grangier, Dan Busbridge et al.
Causal Attribution Analysis for Continuous Outcomes
Shanshan Luo, Yu yixuan, Chunchen LIU et al.
Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs
Luca Arnaboldi, Yatin Dandi, FLORENT KRZAKALA et al.
Outlier-Aware Post-Training Quantization for Discrete Graph Diffusion Models
Zheng Gong, Ying Sun
Ensemble Distribution Distillation via Flow Matching
Jonggeon Park, Giung Nam, Hyunsu Kim et al.
Bayesian Active Learning for Bivariate Causal Discovery
Yuxuan Wang, Mingzhou Liu, Xinwei Sun et al.
Rethinking Addressing in Language Models via Contextualized Equivariant Positional Encoding
Jiajun Zhu, Peihao Wang, Ruisi Cai et al.
On Statistical Learning Theory for Distributional Inputs
Christian Fiedler, Pierre-François Massiani, Friedrich Solowjow et al.
Less is More: Federated Graph Learning with Alleviating Topology Heterogeneity from A Causal Perspective
Lele Fu, Bowen Deng, Sheng Huang et al.
Towards Realistic Model Selection for Semi-supervised Learning
Muyang Li, Xiaobo Xia, Runze Wu et al.
Finite Time Logarithmic Regret Bounds for Self-Tuning Regulation
Rahul Singh, Akshay Mete, Avik Kar et al.
Safety-Polarized and Prioritized Reinforcement Learning
Ke Fan, Jinpeng Zhang, Xuefeng Zhang et al.
A Unified View of FANOVA: A Comprehensive Bayesian Framework for Component Selection and Estimation
Yosra MARNISSI, Maxime Leiber
Non-parametric Online Change Point Detection on Riemannian Manifolds
Xiuheng Wang, Ricardo Borsoi, Cédric Richard
On the Unexpected Effectiveness of Reinforcement Learning for Sequential Recommendation
Álvaro Labarca Silva, Denis Parra, Rodrigo A Toro Icarte
DFlow: A Generative Model Combining Denoising AutoEncoder and Normalizing Flow for High Fidelity Waveform Generation
Chenfeng Miao, Qingying Zhu, Chen Minchuan et al.
On Online Experimentation without Device Identifiers
Shiv Shankar, Ritwik Sinha, Madalina Fiterau
Competitively Consistent Clustering
Niv Buchbinder, Roie Levin, Yue Yang
From Weight-Based to State-Based Fine-Tuning: Further Memory Reduction on LoRA with Parallel Control
Chi Zhang, REN Lianhai, Jingpu Cheng et al.
Transferable Facial Privacy Protection against Blind Face Restoration via Domain-Consistent Adversarial Obfuscation
Kui Zhang, Hang Zhou, Jie Zhang et al.
Do Bayesian Neural Networks Actually Behave Like Bayesian Models?
Gábor Pituk, Vik Shirvaikar, Tom Rainforth
Phase transitions for the existence of unregularized M-estimators in single index models
Takuya Koriyama, Pierre C Bellec
On the Adversarial Robustness of Multi-Kernel Clustering
Hao Yu, Weixuan Liang, KE LIANG et al.
GPTSwarm: Language Agents as Optimizable Graphs
Mingchen Zhuge, Wenyi Wang, Louis Kirsch et al.
Nonlinear transformers can perform inference-time feature learning
Naoki Nishikawa, Yujin Song, Kazusato Oko et al.
Relational Invariant Learning for Robust Solvation Free Energy Prediction
Yeyun Chen
Continuous Semi-Implicit Models
Longlin Yu, Jiajun Zha, Tong Yang et al.
On the Alignment between Fairness and Accuracy: from the Perspective of Adversarial Robustness
Junyi Chai, Taeuk Jang, Jing Gao et al.
Logistic Variational Bayes Revisited
Michael Komodromos, Marina Evangelou, Sarah Filippi
Robust Spatio-Temporal Centralized Interaction for OOD Learning
Jiaming Ma, Binwu Wang, Pengkun Wang et al.
Decentralized Convex Finite-Sum Optimization with Better Dependence on Condition Numbers
Yuxing Liu, Lesi Chen, Luo Luo
Gradient Flow Provably Learns Robust Classifiers for Orthonormal GMMs
Hancheng Min, Rene Vidal
Learning with Expected Signatures: Theory and Applications
Lorenzo Lucchese, Mikko S. Pakkanen, Almut E. D. Veraart
Diffusion Sampling Correction via Approximately 10 Parameters
Guangyi Wang, Wei Peng, lijiang Li et al.
Balancing Feature Similarity and Label Variability for Optimal Size-Aware One-shot Subset Selection
Abhinab Acharya, Dayou Yu, Qi Yu et al.
Representation Preserving Multiclass Agnostic to Realizable Reduction
Steve Hanneke, Qinglin Meng, Amirreza Shaeiri
Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference
Luca Masserano, Alexander Shen, Michele Doro et al.
NEAR: Neural Electromagnetic Array Response
Yinyan Bu, Jiajie Yu, Kai Zheng et al.
Approximate Differential Privacy of the $\ell_2$ Mechanism
Matthew Joseph, Alex Kulesza, Alexander Yu
TANGO: Clustering with Typicality-Aware Nonlocal Mode-Seeking and Graph-Cut Optimization
Haowen Ma, Zhiguo Long, Hua Meng
Overcoming the Optimizer's Curse: Obtaining Realistic Prescriptions from Neural Networks
Asterios Tsiourvas, Georgia Perakis