UAI A

230 papers

YearTitle / Authors
2025A Fast Optimization View: Reformulating Single Layer Attention in LLM Based on Tensor and SVM Trick, and Solving It in Matrix Multiplication Time.
Yeqi Gao, Zhao Song, Weixin Wang, Junze Yin
2025A Mirror Descent Perspective of Smoothed Sign Descent.
Shuyang Wang, Diego Klabjan
2025A Multivariate Unimodality Test Harnessing the Dip Statistic of Mahalanobis Distances Over Random Projections.
Prodromos Kolyvakis, Aristidis Likas
2025A Parallel Network for LRCT Segmentation and Uncertainty Mitigation with Fuzzy Sets.
Shiyi Wang, Yang Nan, Xiaodan Xing, Yingying Fang, Simon L. F. Walsh, Guang Yang
2025A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction.
Leander Kurscheidt, Paolo Morettin, Roberto Sebastiani, Andrea Passerini, Antonio Vergari
2025A Quantum Information Theoretic Approach to Tractable Probabilistic Models.
Pedro Zuidberg Dos Martires
2025A Trajectory-Based Bayesian Approach to Multi-Objective Hyperparameter Optimization with Epoch-Aware Trade-Offs.
Wenyu Wang, Zheyi Fan, Szu Hui Ng
2025A Trust-Region Method for Graphical Stein Variational Inference.
Liam Pavlovic, David M. Rosen
2025A Unified Data Representation Learning for Non-parametric Two-sample Testing.
Xunye Tian, Liuhua Peng, Zhijian Zhou, Mingming Gong, Arthur Gretton, Feng Liu
2025Accurate and Scalable Stochastic Gaussian Process Regression via Learnable Coreset-based Variational Inference.
Mert Ketenci, Adler J. Perotte, Noémie Elhadad, Iñigo Urteaga
2025Adapting Prediction Sets to Distribution Shifts Without Labels.
Kevin Kasa, Zhiyu Zhang, Heng Yang, Graham W. Taylor
2025Adaptive Human-Robot Collaboration using Type-Based IRL.
Prasanth Sengadu Suresh, Prashant Doshi, Bikramjit Banerjee
2025Adaptive Reward Design for Reinforcement Learning.
Minjae Kwon, Ingy Elsayed-Aly, Lu Feng
2025Adaptive Threshold Sampling for Pure Exploration in Submodular Bandits.
Wenjing Chen, Shuo Xing, Victoria G. Crawford
2025Adversarial Training May Induce Deteriorating Distributions.
Runzhi Tian, Yongyi Mao
2025Aggregating Data for Optimal Learning.
Sushant Agarwal, Yukti Makhija, Rishi Saket, Aravindan Raghuveer
2025An Information-theoretic Perspective of Hierarchical Clustering on Graphs.
Yicheng Pan, Bingchen Fan, Pengyu Long, Feng Zheng
2025An Optimal Algorithm for Strongly Convex Min-Min Optimization.
Dmitry Kovalev, Alexander V. Gasnikov, Grigory Malinovsky
2025Approximate Bayesian Inference via Bitstring Representations.
Aleksanteri M. Sladek, Martin Trapp, Arno Solin
2025Are You Doing Better Than Random Guessing? A Call for Using Negative Controls When Evaluating Causal Discovery Algorithms.
Anne Helby Petersen
2025Asymptotically Optimal Linear Best Feasible Arm Identification with Fixed Budget.
Jie Bian, Vincent Y. F. Tan
2025Augmenting Online RL with Offline Data is All You Need: A Unified Hybrid RL Algorithm Design and Analysis.
Ruiquan Huang, Donghao Li, Chengshuai Shi, Cong Shen, Jing Yang
2025BELIEF - Bayesian Sign Entropy Regularization for LIME Framework.
Revoti Prasad Bora, Philipp Terhörst, Raymond N. J. Veldhuis, Raghavendra Ramachandra, Kiran Bylappa Raja
2025Bayesian Optimization over Bounded Domains with the Beta Product Kernel.
Huy Hoang Nguyen, Han Zhou, Matthew B. Blaschko, Aleksei Tiulpin
2025Bayesian Optimization with Inexact Acquisition: Is Random Grid Search Sufficient?
Hwanwoo Kim, Chong Liu, Yuxin Chen
2025Best Arm Identification with Possibly Biased Offline Data.
Le Yang, Vincent Y. F. Tan, Wang Chi Cheung
2025Best Possible Q-Learning.
Jiechuan Jiang, Zongqing Lu
2025Beyond Invisibility: Learning Robust Visible Watermarks for Stronger Copyright Protection.
Tianci Liu, Tong Yang, Quan Zhang, Qi Lei
2025Beyond Sin-Squared Error: Linear Time Entrywise Uncertainty Quantification for Streaming PCA.
Syamantak Kumar, Shourya Pandey, Purnamrita Sarkar
2025Black-box Optimization with Unknown Constraints via Overparameterized Deep Neural Networks.
Dat Phan-Trong, Hung The Tran, Sunil Gupta
2025Budget Allocation Exploiting Label Correlation between Instances.
Adithya Kulkarni, Mohna Chakraborty, Sihong Xie, Qi Li
2025Building Conformal Prediction Intervals with Approximate Message Passing.
Lucas Clarté, Lenka Zdeborová
2025CATE Estimation With Potential Outcome Imputation From Local Regression.
Ahmed Aloui, Juncheng Dong, Cat Phuoc Le, Vahid Tarokh
2025COS-DPO: Conditioned One-Shot Multi-Objective Fine-Tuning Framework.
Yinuo Ren, Tesi Xiao, Michael Shavlovsky, Lexing Ying, Holakou Rahmanian
2025CP
Putri A. van der Linden, Alexander Timans, Erik J. Bekkers
2025Calibrated Regression Against An Adversary Without Regret.
Shachi Deshpande, Charles Marx, Volodymyr Kuleshov
2025Can a Bayesian Oracle Prevent Harm from an Agent?
Yoshua Bengio, Michael K. Cohen, Nikolay Malkin, Matt MacDermott, Damiano Fornasiere, Pietro Greiner, Younesse Kaddar
2025Causal Discovery for Linear Non-Gaussian Models with Disjoint Cycles.
Mathias Drton, Marina Garrote-López, Niko Nikov, Elina Robeva, Y. Samuel Wang
2025Causal Effect Identification in Heterogeneous Environments from Higher-Order Moments.
Yaroslav Kivva, Sina Akbari, Saber Salehkaleybar, Negar Kiyavash
2025Causal Eligibility Traces for Confounding Robust Off-Policy Evaluation.
Junzhe Zhang, Elias Bareinboim
2025Causal Inference amid Missingness-Specific Independences and Mechanism Shifts.
Johan de Aguas, Leonard Henckel, Johan Pensar, Guido Biele
2025Causal Models for Growing Networks.
Gecia Bravo Hermsdorff, Kayvan Sadeghi, Lee M. Gunderson
2025Coevolutionary Emergent Systems Optimization with Applications to Ultra-High-Dimensional Metasurface Design : OAM Wave Manipulation.
Zhengxuan Jiang, Guowen Ding, Wen Jiang
2025Collaborative Prediction: To Join or To Disjoin Datasets.
Kyung Rok Kim, Yansong Wang, Xiaocheng Li, Guanting Chen
2025Collapsing Sequence-Level Data-Policy Coverage via Poisoning Attack in Offline Reinforcement Learning.
Xue Zhou, Dapeng Man, Chen Xu, Fanyi Zeng, Tao Liu, Huan Wang, Shucheng He, Chaoyang Gao, Wu Yang
2025Complete Characterization for Adjustment in Summary Causal Graphs of Time Series.
Clément Yvernes, Emilie Devijver, Éric Gaussier
2025Computationally Efficient Methods for Invariant Feature Selection with Sparsity.
Jane Du, Arindam Banerjee
2025Concept Forgetting via Label Annealing.
Subhodip Panda, Ananda Theertha Suresh, Atri Guha, Prathosh A. P.
2025Conditional Average Treatment Effect Estimation Under Hidden Confounders.
Ahmed Aloui, Juncheng Dong, Ali Hasan, Vahid Tarokh
2025Conference on Uncertainty in Artificial Intelligence, Rio Othon Palace, Rio de Janeiro, Brazil, 21-25 July 2025.
Silvia Chiappa, Sara Magliacane
2025Conformal Prediction Sets for Deep Generative Models via Reduction to Conformal Regression.
Hooman Shahrokhi, Devjeet Raj Roy, Yan Yan, Venera Arnaoudova, Jana Doppa
2025Conformal Prediction for Federated Graph Neural Networks with Missing Neighbor Information.
Ömer Faruk Akgül, Rajgopal Kannan, Viktor K. Prasanna
2025Conformal Prediction without Nonconformity Scores.
Jonas Hanselle, Alireza Javanmardi, Tobias Florin Oberkofler, Yusuf Sale, Eyke Hüllermeier
2025Constraint-based Causal Discovery from a Collection of Conditioning Sets.
Kenneth Lee, Bruno Ribeiro, Murat Kocaoglu
2025Contaminated Multivariate Time-Series Anomaly Detection with Spatio-Temporal Graph Conditional Diffusion Models.
Thi Kieu Khanh Ho, Narges Armanfard
2025Contrast-CAT: Contrasting Activations for Enhanced Interpretability in Transformer-based Text Classifiers.
Sungmin Han, Jeonghyun Lee, Sangkyun Lee
2025Correlated Quantization for Faster Nonconvex Distributed Optimization.
Andrei Panferov, Yury Demidovich, Ahmad Rammal, Peter Richtárik
2025Corruption-Robust Variance-aware Algorithms for Generalized Linear Bandits under Heavy-tailed Rewards.
Qingyuan Yu, Euijin Baek, Xiang Li, Qiang Sun
2025Creative Agents: Empowering Agents with Imagination for Creative Tasks.
Penglin Cai, Chi Zhang, Yuhui Fu, Haoqi Yuan, Zongqing Lu
2025Critical Influence of Overparameterization on Sharpness-aware Minimization.
Sungbin Shin, Dongyeop Lee, Maksym Andriushchenko, Namhoon Lee
2025Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated Learning.
Francesco Diana, André Nusser, Chuan Xu, Giovanni Neglia
2025DF
Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang
2025Decomposition of Probabilities of Causation with Two Mediators.
Yuta Kawakami, Jin Tian
2025Dependent Randomized Rounding for Budget Constrained Experimental Design.
Khurram Yamin, Edward Kennedy, Bryan Wilder
2025Discriminative ordering through ensemble consensus.
Louis Ohl, Fredrik Lindsten
2025Distributional Reinforcement Learning with Dual Expectile-Quantile Regression.
Sami Jullien, Romain Deffayet, Jean-Michel Renders, Paul Groth, Maarten de Rijke
2025Distributionally and Adversarially Robust Logistic Regression via Intersecting Wasserstein Balls.
Aras Selvi, Eleonora Kreacic, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
2025Divide and Orthogonalize: Efficient Continual Learning with Local Model Space Projection.
Jin Shang, Simone Shao, Tian Tong, Fan Yang, Yetian Chen, Yang Jiao, Jia Liu, Yan Gao
2025Do Vendi Scores Converge with Finite Samples? Truncated Vendi Score for Finite-Sample Convergence Guarantees.
Azim Ospanov, Farzan Farnia
2025DyGMAE: A Novel Dynamic Graph Masked Autoencoder for Link Prediction.
Weixiong Liu, Junwei Cheng, Zhongyu Pan, Chaobo He, Quanlong Guan
2025Dynamic Maintenance of Kernel Density Estimation Data Structure: From Practice to Theory.
Jiehao Liang, Zhao Song, Zhaozhuo Xu, Junze Yin, Danyang Zhuo
2025EERO: Early Exit with Reject Option for Efficient Classification with limited budget.
Florian Valade, Mohamed Hebiri, Paul Gay
2025ELBO, regularized maximum likelihood, and their common one-sample approximation for training stochastic neural networks.
Sina Däubener, Simon Damm, Asja Fischer
2025ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression.
Avetik G. Karagulyan, Peter Richtárik
2025Efficient Algorithms for Logistic Contextual Slate Bandits with Bandit Feedback.
Tanmay Goyal, Gaurav Sinha
2025Efficiently Escaping Saddle Points for Policy Optimization.
Mohammadsadegh Khorasani, Saber Salehkaleybar, Negar Kiyavash, Niao He, Matthias Grossglauser
2025Enhanced Equilibria-Solving via Private Information Pre-Branch Structure in Adversarial Team Games.
Chen Qiu, Haobo Fu, Kai Li, Jiajia Zhang, Xuan Wang
2025Enhancing Uncertainty Quantification in Large Language Models through Semantic Graph Density.
Zhaoye Li, Siyuan Shen, Wenjing Yang, Ruochun Jin, Huan Chen, Ligong Cao, Jing Ren
2025Enumerating Optimal Cost-Constrained Adjustment Sets.
Batya Kenig
2025Epistemic Uncertainty in Conformal Scores: A Unified Approach.
Luben M. C. Cabezas, Vagner S. Santos, Thiago R. Ramos, Rafael Izbicki
2025Error Bounds for Physics-Informed Neural Networks in Fokker-Planck PDEs.
Chun-Wei Kong, Luca Laurenti, Jay W. McMahon, Morteza Lahijanian
2025Evasion Attacks Against Bayesian Predictive Models.
Pablo G. Arce, Roi Naveiro, David Ríos Insua
2025Experimentation under Treatment Dependent Network Interference.
Shiv Shankar, Ritwik Sinha, Madalina Fiterau
2025Expert-In-The-Loop Causal Discovery: Iterative Model Refinement Using Expert Knowledge.
Ankur Ankan, Johannes Textor
2025Explaining Negative Classifications of AI Models in Tumor Diagnosis.
David A. Kelly, Hana Chockler, Nathan Blake
2025Exploring Exploration in Bayesian Optimization.
Leonard Papenmeier, Nuojin Cheng, Stephen Becker, Luigi Nardi
2025FALCON: Adaptive Cross-Domain APT Attack Investigation with Federated Causal Learning.
Jialu Tang, Yali Gao, Xiaoyong Li, Jiawei Li, Shui Yu, Binxing Fang
2025FDR-SVM: A Federated Distributionally Robust Support Vector Machine via a Mixture of Wasserstein Balls Ambiguity Set.
Michael Ibrahim, Heraldo Rozas, Nagi Gebraeel, Weijun Xie
2025Fast Calculation of Feature Contributions in Boosting Trees.
Zhongli Jiang, Min Zhang, Dabao Zhang
2025Fast Non-convex Matrix Sensing with Optimal Sample Complexity.
Jian-Feng Cai, Tong Wu, Ruizhe Xia
2025FeDCM: Federated Learning of Deep Causal Generative Models.
Md. Musfiqur Rahman, Murat Kocaoglu
2025FedSPD: A Soft-clustering Approach for Personalized Decentralized Federated Learning.
I-Cheng Lin, Osman Yagan, Carlee Joe-Wong
2025Federated Rényi Fair Inference in Federated Heterogeneous System.
Zhiyong Ma, Yuanjie Shi, Yan Yan, Jian Chen
2025Finding Interior Optimum of Black-box Constrained Objective with Bayesian Optimization.
Fengxue Zhang, Yuxin Chen
2025Flat Posterior Does Matter For Bayesian Model Averaging.
Sungjun Lim, Jeyoon Yeom, Sooyon Kim, Hoyoon Byun, Jinho Kang, Yohan Jung, Jiyoung Jung, Kyungwoo Song
2025FlightPatchNet: Multi-Scale Patch Network with Differential Coding for Short-Term Flight Trajectory Prediction.
Lan Wu, Xuebin Wang, Ruijuan Chu, Guangyi Liu, Jing Zhang, Linyu Wang
2025Flow-Based Delayed Hawkes Process.
Chao Yang, Wendi Ren, Shuang Li
2025Full Network Capacity Framework for Sample-Efficient Deep Reinforcement Learning.
Wentao Yang, Xinyue Liu, Yunlong Gao, Wenxin Liang, Linlin Zong, Guanglu Wang, Xianchao Zhang
2025Generalised Probabilistic Modelling and Improved Uncertainty Estimation in Comparative LLM-as-a-judge.
Yassir Fathullah, Mark J. F. Gales
2025Generative Uncertainty in Diffusion Models.
Metod Jazbec, Eliot Wong-Toi, Guoxuan Xia, Dan Zhang, Eric T. Nalisnick, Stephan Mandt
2025Geodesic Slice Sampler for Multimodal Distributions with Strong Curvature.
Bernardo Williams, Hanlin Yu, Hoang Phuc Hau Luu, Georgios Arvanitidis, Arto Klami
2025Group-Agent Reinforcement Learning with Heterogeneous Agents.
Kaiyue Wu, Xiao-Jun Zeng, Tingting Mu
2025Guaranteed Prediction Sets for Functional Surrogate Models.
Ander Gray, Vignesh Gopakumar, Sylvain Rousseau, Sébastien Destercke
2025Guiding Time-Varying Generative Models with Natural Gradients on Exponential Family Manifold.
Song Liu, Leyang Wang, Yakun Wang
2025HDP-Flow: Generalizable Bayesian Nonparametric Model for Time Series State Discovery.
Sana Tonekaboni, Tina Behrouzi, Addison Weatherhead, Emily B. Fox, David M. Blei, Anna Goldenberg
2025Hindsight Merging: Diverse Data Generation with Language Models.
Veniamin Veselovsky, Benedikt Stroebl, Gianluca M. Bencomo, Dilip Arumugam, Lisa Schut, Arvind Narayanan, Thomas L. Griffiths
2025How Likely Are Two Voting Rules Different?
Ziqi Yu, Lirong Xia, Qishen Han, Chengkai Zhang
2025Hybrid Bernstein Normalizing Flows for Flexible Multivariate Density Regression with Interpretable Marginals.
Marcel Arpogaus, Thomas Kneib, Thomas Nagler, David Rügamer
2025Improved Uncertainty Quantification in Physics-Informed Neural Networks Using Error Bounds and Solution Bundles.
Pablo Flores, Olga Graf, Pavlos Protopapas, Karim Pichara
2025Improved Variational Inference in Discrete VAEs using Error Correcting Codes.
María Martínez-García, Grace Villacrés, David G. M. Mitchell, Pablo M. Olmos
2025Improving Adversarial Transferability via Decision Boundary Adaptation.
Jiayu Zhang, Zhiyu Zhu, Zhibo Jin, Xinyi Wang, Huaming Chen, Kim-Kwang Raymond Choo
2025Improving Graph Contrastive Learning with Community Structure.
Xiang Chen, Kun Yue, Liang Duan, Lixing Yu
2025InfoDPCCA: Information-Theoretic Dynamic Probabilistic Canonical Correlation Analysis.
Shiqin Tang, Shujian Yu
2025Informative Synthetic Data Generation for Thorax Disease Classification.
Yancheng Wang, Rajeev Goel, Marko Jojic, Alvin C. Silva, Teresa Wu, Yingzhen Yang
2025Instance-Wise Monotonic Calibration by Constrained Transformation.
Yunrui Zhang, Gustavo Enrique Batista, Salil S. Kanhere
2025Just Trial Once: Ongoing Causal Validation of Machine Learning Models.
Jacob M. Chen, Michael Oberst
2025Label Distribution Learning using the Squared Neural Family on the Probability Simplex.
Daokun Zhang, Russell Tsuchida, Dino Sejdinovic
2025Learning Algorithms for Multiple Instance Regression.
Aaryan Gupta, Rishi Saket
2025Learning Causal Response Representations through Direct Effect Analysis.
Homer Durand, Gherardo Varando, Gustau Camps-Valls
2025Learning Multi-interest Embedding with Dynamic Graph Cluster for Sequention Recommendation.
Chunjing Xiao, Ranhao Guo, Zhang Yongwang, Xiaoming Wu
2025Learning Robust XGBoost Ensembles for Regression Tasks.
Atri Vivek Sharma, Panagiotis Kouvaros, Alessio Lomuscio
2025Learning from Label Proportions and Covariate-shifted Instances.
Sagalpreet Singh, Navodita Sharma, Shreyas Havaldar, Rishi Saket, Aravindan Raghuveer
2025Learning to Sample in Stochastic Optimization.
Sijia Zhou, Yunwen Lei, Ata Kabán
2025Learning to Stabilize Unknown LTI Systems on a Single Trajectory under Stochastic Noise.
Ziyi Zhang, Yorie Nakahira, Guannan Qu
2025Learning with Confidence.
Oliver E. Richardson
2025Letting Uncertainty Guide Your Multimodal Machine Translation.
Wuyi Liu, Yue Gao, Yige Mao, Jing Zhao
2025Limit-sure Reachability for Small Memory Policies in POMDPs is NP-complete.
Ali Asadi, Krishnendu Chatterjee, Raimundo Saona, Ali Shafiee
2025LoSAM: Local Search in Additive Noise Models with Mixed Mechanisms and General Noise for Global Causal Discovery.
Sujai Hiremath, Promit Ghosal, Kyra Gan
2025Lower Bound on Howard Policy Iteration for Deterministic Markov Decision Processes.
Ali Asadi, Krishnendu Chatterjee, Jakob de Raaij
2025Lower Bounds on the Size of Markov Equivalence Classes.
Erik Jahn, Frederick Eberhardt, Leonard J. Schulman
2025MOHITO: Multi-Agent Reinforcement Learning using Hypergraphs for Task-Open Systems.
Gayathri Anil, Prashant Doshi, Daniel Redder, Adam Eck, Leen-Kiat Soh
2025MSCGrapher: Learning Multi-Scale Dynamic Correlations for Multivariate Time Series Forecasting.
Xian Yang, Zhenguo Zhang, Shihao Lu
2025MSP-SR: Multi-Stage Probabilistic Generative Super Resolution with Scarce High-Resolution Data.
Ruike Zhu, Matthew Charles Weston, Hanwen Zhang, Arindam Banerjee
2025Measuring IIA Violations in Similarity Choices with Bayesian Models.
Hugo Sales Correa, Suryanarayana Sankagiri, Daniel R. Figueiredo, Matthias Grossglauser
2025Metric Learning in an RKHS.
Gokcan Tatli, Yi Chen, Blake Mason, Robert D. Nowak, Ramya Korlakai Vinayak
2025MindFlayer SGD: Efficient Parallel SGD in the Presence of Heterogeneous and Random Worker Compute Times.
Arto Maranjyan, Omar Shaikh Omar, Peter Richtárik
2025Minimax Optimal Nonsmooth Nonparametric Regression via Fractional Laplacian Eigenmaps.
Zhaoyang Shi, Krishna Balasubramanian, Wolfgang Polonik
2025Mixup Regularization: A Probabilistic Perspective.
Yousef El-Laham, Niccolò Dalmasso, Svitlana Vyetrenko, Vamsi K. Potluru, Manuela Veloso
2025Moment Alignment: Unifying Gradient and Hessian Matching for Domain Generalization.
Yuen Chen, Haozhe Si, Guojun Zhang, Han Zhao
2025Moments of Causal Effects.
Yuta Kawakami, Jin Tian
2025Multi-Cost-Bounded Reachability Analysis of POMDPs.
Alexander Bork, Joost-Pieter Katoen, Tim Quatmann, Svenja Stein
2025Multi-Label Bayesian Active Learning with Inter-Label Relationships.
Yuanyuan Qi, Jueqing Lu, Xiaohao Yang, Joanne Enticott, Lan Du
2025Multi-armed Bandits with Missing Outcomes.
Ilia Mahrooghi, Mahshad Moradi, Sina Akbari, Negar Kiyavash
2025Multi-group Uncertainty Quantification for Long-form Text Generation.
Terrance Liu, Steven Wu
2025Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization.
Dai Hai Nguyen, Hiroshi Mamitsuka, Atsuyoshi Nakamura
2025MutualNeRF: Improve the Performance of NeRF under Limited Samples with Mutual Information Theory.
Zifan Wang, Jingwei Li, Yitang Li, Yunze Liu
2025NRFlow: Towards Noise-Robust Generative Modeling via High-Order Mechanism.
Bo Chen, Chengyue Gong, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Mingda Wan, Xugang Ye
2025Near-Optimal Regret Bounds for Federated Multi-armed Bandits with Fully Distributed Communication.
Haoran Zhang, Xuchuang Wang, Hao-Xu Chen, Hao Qiu, Lin Yang, Yang Gao
2025Nearly Optimal Differentially Private ReLU Regression.
Meng Ding, Mingxi Lei, Shaowei Wang, Tianhang Zheng, Di Wang, Jinhui Xu
2025Nonlinear Causal Discovery for Grouped Data.
Konstantin Göbler, Tobias Windisch, Mathias Drton
2025Nonparametric Bayesian Multi-Facet Clustering for Longitudinal Data.
Luwei Wang, Kieran Richards, Sohan Seth
2025Nonparametric Bayesian inference of item-level features in classifier combination.
Patrick Stinson, Nikolaus Kriegeskorte
2025ODD: Overlap-aware Estimation of Model Performance under Distribution Shift.
Aayush Mishra, Anqi Liu
2025Off-policy Predictive Control with Causal Sensitivity Analysis.
Myrl G. Marmarelis, Ali Hasan, Kamyar Azizzadenesheli, R. Michael Alvarez, Anima Anandkumar
2025Offline Changepoint Detection With Gaussian Processes.
Janneke Verbeek, Tom Heskes, Yuliya Shapovalova
2025On Constant Regret for Low-Rank MDPs.
Alexander Sturm, Sebastian Tschiatschek
2025On Continuous Monitoring of Risk Violations under Unknown Shift.
Alexander Timans, Rajeev Verma, Eric T. Nalisnick, Christian A. Naesseth
2025On Information-Theoretic Measures of Predictive Uncertainty.
Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Sepp Hochreiter
2025On the Privacy Risks of Spiking Neural Networks: A Membership Inference Analysis.
Junyi Guan, Abhijith Sharma, Chong Tian, Salem Lahlou
2025Online Generalized Magician's Problem with Multiple Workers.
Ruoyu Wu, Wei Bao, Ben Liang, Liming Ge
2025Online Learning with Stochastically Partitioning Experts.
Puranjay Datta, Sharayu Moharir, Jaya Prakash Champati
2025Optimal Submanifold Structure in Log-linear Models.
Zhou Derun, Mahito Sugiyama
2025Optimal Transport Alignment of User Preferences from Ratings and Texts.
Nhu-Thuat Tran, Hady W. Lauw
2025Optimal Transport for Probabilistic Circuits.
Adrian Ciotinga, YooJung Choi
2025Optimal Zero-shot Regret Minimization for Selective Classification with Out-of-Distribution Detection.
Eduardo Dadalto Câmara Gomes, Marco Romanelli
2025Order-Optimal Global Convergence for Actor-Critic with General Policy and Neural Critic Parametrization.
Swetha Ganesh, Jiayu Chen, Washim Uddin Mondal, Vaneet Aggarwal
2025Out-of-distribution Robust Optimization.
Zhongze Cai, Hansheng Jiang, Xiaocheng Li
2025Over the Top-1: Uncertainty-Aware Cross-Modal Retrieval with CLIP.
Lluis Gomez
2025Partial-Label Learning with Conformal Candidate Cleaning.
Tobias Fuchs, Florian Kalinke
2025Periodical Moving Average Accelerates Gradient Accumulation for Post-Training.
Yumou Liu, An Li, Chaojie Li, Fei Yu, Benyou Wang
2025Privacy-Preserving Neural Processes for Probabilistic User Modeling.
Amir Sonee, Haripriya Harikumar, Alex Hämäläinen, Lukas Prediger, Samuel Kaski
2025Probabilistic Embeddings for Frozen Vision-Language Models: Uncertainty Quantification with Gaussian Process Latent Variable Models.
Aishwarya Venkataramanan, Paul Bodesheim, Joachim Denzler
2025Probabilistic Explanations for Regression Models.
Frédéric Koriche, Jean-Marie Lagniez, Chi Tran
2025Probabilistic Graph Circuits: Deep Generative Models for Tractable Probabilistic Inference over Graphs.
Milan Papez, Martin Rektoris, Václav Smídl, Tomás Pevný
2025Probabilistic Semantics Guided Discovery of Approximate Functional Dependencies.
Liang Duan, Xinran Wu, Xinhui Li, Lixing Yu, Kun Yue
2025Probability-Raising Causality for Uncertain Parametric Markov Decision Processes with PAC Guarantees.
Ryohei Oura, Yuji Ito
2025Provably Adaptive Average Reward Reinforcement Learning for Metric Spaces.
Avik Kar, Rahul Singh
2025Proximal Interacting Particle Langevin Algorithms.
Paula Cordero-Encinar, Francesca R. Crucinio, Ömer Deniz Akyildiz
2025Proxy-informed Bayesian transfer learning with unknown sources.
Sabina J. Sloman, Julien Martinelli, Samuel Kaski
2025Pure and Strong Nash Equilibrium Computation in Compactly Representable Aggregate Games.
Jared Soundy, Mohammad T. Irfan, Hau Chan
2025Quantum Speedups for Bayesian Network Structure Learning.
Juha Harviainen, Kseniya Rychkova, Mikko Koivisto
2025RCAP: Robust, Class-Aware, Probabilistic Dynamic Dataset Pruning.
Atif Hassan, Swanand R. Khare, Jiaul H. Paik
2025RDI: An adversarial robustness evaluation metric for deep neural networks based on model statistical features.
Jialei Song, Xingquan Zuo, Feiyang Wang, Hai Huang, Tianle Zhang
2025RL, but don't do anything I wouldn't do.
Michael K. Cohen, Marcus Hutter, Yoshua Bengio, Stuart Russell
2025Relational Causal Discovery with Latent Confounders.
Matteo Negro, Andrea Piras, Ragib Ahsan, David Arbour, Elena Zheleva
2025Reparameterizing Hybrid Markov Logic Networks to handle Covariate-Shift in Representations.
Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal
2025Residual Reweighted Conformal Prediction for Graph Neural Networks.
Zheng Zhang, Jie Bao, Zhixin Zhou, Nicolò Colombo, Lixin Cheng, Rui Luo
2025Revisiting the Berkeley Admissions data: Statistical Tests for Causal Hypotheses.
Sourbh Bhadane, Joris M. Mooij, Philip A. Boeken, Onno Zoeter
2025Revisiting the Equivalence of Bayesian Neural Networks and Gaussian Processes: On the Importance of Learning Activations.
Marcin Sendera, Amin Sorkhei, Tomasz Kusmierczyk
2025Robust Optimization with Diffusion Models for Green Security.
Lingkai Kong, Haichuan Wang, Yuqi Pan, Cheol Woo Kim, Mingxiao Song, Alayna Nguyen, Tonghan Wang, Haifeng Xu, Milind Tambe
2025Root Cause Analysis of Failures from Partial Causal Structures.
Azam Ikram, Kenneth Lee, Shubham Agarwal, Shiv Kumar Saini, Saurabh Bagchi, Murat Kocaoglu
2025SALSA: A Secure, Adaptive and Label-Agnostic Scalable Algorithm for Machine Unlearning.
Owais Makroo, Atif Hassan, Swanand R. Khare
2025SPvR: Structured Pruning via Ranking.
Atif Hassan, Jiaul H. Paik, Swanand R. Khare
2025STIMULUS: Achieving Fast Convergence and Low Sample Complexity in Stochastic Multi-Objective Learning.
Zhuqing Liu, Chaosheng Dong, Michinari Momma, Simone Shao, Shaoyuan Xu, Yan Gao, Haibo Yang, Jia Liu
2025Sample and Computationally Efficient Continuous-Time Reinforcement Learning with General Function Approximation.
Runze Zhao, Yue Yu, Adams Yiyue Zhu, Chen Yang, Dongruo Zhou
2025Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference.
Colin Samplawski, Adam D. Cobb, Manoj Acharya, Ramneet Kaur, Susmit Jha
2025Scaling Probabilistic Circuits via Data Partitioning.
Jonas Seng, Florian Peter Busch, Pooja Prasad, Devendra Singh Dhami, Martin Mundt, Kristian Kersting
2025Selective Blocking for Message-Passing Neural Networks on Heterophilic Graphs.
Yoonhyuk Choi, Taewook Ko, Jiho Choi, Chong-Kwon Kim
2025Simulation-Free Differential Dynamics Through Neural Conservation Laws.
Mengjian Hua, Eric Vanden-Eijnden, Ricky T. Q. Chen
2025Simulation-based Inference for High-dimensional Data using Surjective Sequential Neural Likelihood Estimation.
Simon Dirmeier, Carlo Albert, Fernando Pérez-Cruz
2025Sparse Structure Exploration and Re-optimization for Vision Transformer.
Sangho An, Jinwoo Kim, Keonho Lee, Jingang Huh, Chanwoong Kwak, Yujin Lee, Moonsub Jin, Jangho Kim
2025SpinSVAR: Estimating Structural Vector Autoregression Assuming Sparse Input.
Panagiotis Misiakos, Markus Püschel
2025Statistical Significance of Feature Importance Rankings.
Jeremy Goldwasser, Giles Hooker
2025Stein Variational Evolution Strategies.
Cornelius V. Braun, Robert Tjarko Lange, Marc Toussaint
2025Stochastic Embeddings : A Probabilistic and Geometric Analysis of Out-of-Distribution Behavior.
Anthony Nguyen, Emanuel Aldea, Sylvie Le Hégarat-Mascle, Renaud Lustrat
2025Symbiotic Local Search for Small Decision Tree Policies in MDPs.
Roman Andriushchenko, Milan Ceska, Debraj Chakraborty, Sebastian Junges, Jan Kretínský, Filip Macák
2025Targeted Learning for Variable Importance.
Xiaohan Wang, Yunzhe Zhou, Giles Hooker
2025Temperature Optimization for Bayesian Deep Learning.
Kenyon Ng, Chris van der Heide, Liam Hodgkinson, Susan Wei
2025Testing Generalizability in Causal Inference.
Daniel de Vassimon Manela, Linying Yang, Robin J. Evans
2025The Causal Information Bottleneck and Optimal Causal Variable Abstractions.
Francisco Nunes Ferreira Quialheiro Simoes, Mehdi Dastani, Thijs van Ommen
2025The Consistency Hypothesis in Uncertainty Quantification for Large Language Models.
Quan Xiao, Debarun Bhattacharjya, Balaji Ganesan, Radu Marinescu, Katsiaryna Mirylenka, Nhan H. Pham, Michael R. Glass, Junkyu Lee
2025The Relativity of Causal Knowledge.
Gabriele D'Acunto, Claudio Battiloro
2025Toward Universal Laws of Outlier Propagation.
Aram Ebtekar, Yuhao Wang, Dominik Janzing
2025Towards Provably Efficient Learning of Imperfect Information Extensive-Form Games with Linear Function Approximation.
Canzhe Zhao, Shuze Chen, Weiming Liu, Haobo Fu, Qiang Fu, Shuai Li
2025Trading Off Voting Axioms for Privacy.
Zhechen Li, Ao Liu, Lirong Xia, Yongzhi Cao, Hanpin Wang
2025Transparent Trade-offs between Properties of Explanations.
Hiwot Belay Tadesse, Alihan Hüyük, Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez
2025Truthful Elicitation of Imprecise Forecasts.
Anurag Singh, Siu Lun Chau, Krikamol Muandet
2025Tuning Algorithmic and Architectural Hyperparameters in Graph-Based Semi-Supervised Learning with Provable Guarantees.
Ally Yalei Du, Eric Huang, Dravyansh Sharma
2025Tuning-Free Coreset Markov Chain Monte Carlo via Hot DoG.
Naitong Chen, Jonathan H. Huggins, Trevor Campbell
2025Unsupervised Attributed Dynamic Network Embedding with Stability Guarantees.
Emma Ceccherini, Ian Gallagher, Andrew Jones, Daniel John Lawson
2025Using Submodular Optimization to Approximate Minimum-Size Abductive Path Explanations for Tree-Based Models.
Louenas Bounia
2025VADIS: Investigating Inter-View Representation Biases for Multi-View Partial Multi-Label Learning.
Jie Wang, Ning Xu, Xin Geng
2025Valid Bootstraps for Network Embeddings with Applications to Network Visualisation.
Emerald Dilworth, Ed Davis, Daniel John Lawson
2025Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling.
Jian Xu, Shian Du, Junmei Yang, Qianli Ma, Delu Zeng, John Paisley
2025Weak to Strong Learning from Aggregate Labels.
Yukti Makhija, Rishi Saket
2025Well-Defined Function-Space Variational Inference in Bayesian Neural Networks via Regularized KL-Divergence.
Tristan Cinquin, Robert Bamler
2025What is the Right Notion of Distance between Predict-then-Optimize Tasks?
Paula Rodriguez Diaz, Lingkai Kong, Kai Wang, David Alvarez-Melis, Milind Tambe
2025When Extragradient Meets PAGE: Bridging Two Giants to Boost Variational Inequalities.
Gleb Molodtsov, Valery Parfenov, Egor Petrov, Grigoriy Evseev, Daniil Medyakov, Aleksandr Beznosikov
2025i
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2025σ-Maximal Ancestral Graphs.
Binghua Yao, Joris M. Mooij