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UAI 2024

A

Conference on Uncertainty in Artificial Intelligence

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201
accepted papers
734
authors
July 15-19, 2024
dates
Spain
location

201 / 201 papers

  1. 1
    A General Identification Algorithm For Data Fusion Problems Under Systematic Selection
    Jaron Jia Rong Lee
    ,
    AmirEmad Ghassami
    ,
    Ilya Shpitser
  2. 2
    A Generalized Bayesian Approach to Distribution-on-Distribution Regression
    Tin Lok James Ng
  3. 3
    A Global Markov Property for Solutions of Stochastic Difference Equations and the corresponding Full Time Graphs
    Tom Hochsprung
    ,
    Jakob Runge
    ,
    Andreas Gerhardus
  4. 4
    A Graph Theoretic Approach for Preference Learning with Feature Information
    Aadirupa Saha
    ,
    Arun Rajkumar
  5. 5
    A Homogenization Approach for Gradient-Dominated Stochastic Optimization
    Jiyuan Tan
    ,
    Chenyu Xue
    ,
    Chuwen Zhang
    ,
    Qi Deng
    ,
    Dongdong Ge
    ,
    Yinyu Ye
  6. 6
    Active Learning Framework for Incomplete Networks
    Tung Khong
    ,
    Cong Tran
    ,
    Cuong Pham
  7. 7
    Adaptive Softmax Trees for Many-Class Classification
    Rasul Kairgeldin
    ,
    Magzhan Gabidolla
    ,
    Miguel Á. Carreira-Perpiñán
  8. 8
    Adaptive Time-Stepping Schedules for Diffusion Models
    Yuzhu Chen
    ,
    Fengxiang He
    ,
    Shi Fu
    ,
    Xinmei Tian
    ,
    Dacheng Tao
  9. 9
    Adjustment Identification Distance: A gadjid for Causal Structure Learning
    Leonard Henckel
    ,
    Theo Würtzen
    ,
    Sebastian Weichwald
  10. 10
    Amortized Variational Inference: When and Why?
    Charles C. Margossian
    ,
    David M. Blei
  11. 11
    Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression
    Lucas Clarté
    ,
    Adrien Vandenbroucque
    ,
    Guillaume Dalle
    ,
    Bruno Loureiro
    ,
    Florent Krzakala
    ,
    Lenka Zdeborová
  12. 12
    Anomaly Detection with Variance Stabilized Density Estimation
    Amit Rozner
    ,
    Barak Battash
    ,
    Henry Li
    ,
    Lior Wolf
    ,
    Ofir Lindenbaum
  13. 13
    Approximate Bayesian Computation with Path Signatures
    Joel Dyer
    ,
    Patrick Cannon
    ,
    Sebastian M. Schmon
  14. 14
    Approximate Kernel Density Estimation under Metric-based Local Differential Privacy
    Yi Zhou
    ,
    Yanhao Wang
    ,
    Long Teng
    ,
    Qiang Huang
    ,
    Cen Chen
  15. 15
    Approximation Algorithms for Observer Aware MDPs
    Shuwa Miura
    ,
    Olivier Buffet
    ,
    Shlomo Zilberstein
  16. 16
    AutoDrop: Training Deep Learning Models with Automatic Learning Rate Drop
    Jing Wang
    ,
    Yunfei Teng
    ,
    Anna Choromanska
  17. 17
    BanditQ: Fair Bandits with Guaranteed Rewards
    Abhishek Sinha
  18. 18
    Bandits with Knapsacks and Predictions
    Davide Drago
    ,
    Andrea Celli
    ,
    Marek Eliás
  19. 19
    Base Models for Parabolic Partial Differential Equations
    Xingzi Xu
    ,
    Ali Hasan
    ,
    Jie Ding
    ,
    Vahid Tarokh
  20. 20
    Bayesian Active Learning in the Presence of Nuisance Parameters
    Sabina J. Sloman
    ,
    Ayush Bharti
    ,
    Julien Martinelli
    ,
    Samuel Kaski
  21. 21
    Bayesian Pseudo-Coresets via Contrastive Divergence
    Piyush Tiwary
    ,
    Kumar Shubham
    ,
    Vivek Kashyap
    ,
    Prathosh A. P.
  22. 22
    BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts
    Emanuele Marconato
    ,
    Samuele Bortolotti
    ,
    Emile van Krieken
    ,
    Antonio Vergari
    ,
    Andrea Passerini
    ,
    Stefano Teso
  23. 23
    Beyond Dirichlet-based Models: When Bayesian Neural Networks Meet Evidential Deep Learning
    Hanjing Wang
    ,
    Qiang Ji
  24. 24
    Bias-aware Boolean Matrix Factorization Using Disentangled Representation Learning
    Xiao Wang
    ,
    Jia Wang
    ,
    Tong Zhao
    ,
    Yijie Wang
    ,
    Nan Zhang
    ,
    Yong Zang
    ,
    Sha Cao
    ,
    Chi Zhang
  25. 25
    Bootstrap Your Conversions: Thompson Sampling for Partially Observable Delayed Rewards
    Marco Gigli
    ,
    Fabio Stella
  26. 26
    Bounding causal effects with leaky instruments
    David S. Watson
    ,
    Jordan Penn
    ,
    Lee M. Gunderson
    ,
    Gecia Bravo Hermsdorff
    ,
    Afsaneh Mastouri
    ,
    Ricardo Silva
  27. 27
    Calibrated and Conformal Propensity Scores for Causal Effect Estimation
    Shachi Deshpande
    ,
    Volodymyr Kuleshov
  28. 28
    Can we Defend Against the Unknown? An Empirical Study About Threshold Selection for Neural Network Monitoring
    Khoi Tran Dang
    ,
    Kevin Delmas
    ,
    Jérémie Guiochet
    ,
    Joris Guérin
  29. 29
    Causal Discovery with Deductive Reasoning: One Less Problem
    Jonghwan Kim
    ,
    Inwoo Hwang
    ,
    Sanghack Lee
  30. 30
    Causally Abstracted Multi-armed Bandits
    Fabio Massimo Zennaro
    ,
    Nicholas Bishop
    ,
    Joel Dyer
    ,
    Yorgos Felekis
    ,
    Anisoara Calinescu
    ,
    Michael J. Wooldridge
    ,
    Theodoros Damoulas
  31. 31
    Center-Based Relaxed Learning Against Membership Inference Attacks
    Xingli Fang
    ,
    Jung-Eun Kim
  32. 32
    Characterising Interventions in Causal Games
    Manuj Mishra
    ,
    James Fox
    ,
    Michael J. Wooldridge
  33. 33
    Characterizing Data Point Vulnerability as Average-Case Robustness
    Tessa Han
    ,
    Suraj Srinivas
    ,
    Himabindu Lakkaraju
  34. 34
    Cold-start Recommendation by Personalized Embedding Region Elicitation
    Hieu Trung Nguyen
    ,
    Duy Nguyen
    ,
    Khoa D. Doan
    ,
    Viet Anh Nguyen
  35. 35
    Common Event Tethering to Improve Prediction of Rare Clinical Events
    Quinn Lanners
    ,
    Qin Weng
    ,
    Marie-Louise Meng
    ,
    Matthew M. Engelhard
  36. 36
    Computing Low-Entropy Couplings for Large-Support Distributions
    Samuel Sokota
    ,
    Dylan Sam
    ,
    Christian Schröder de Witt
    ,
    Spencer Compton
    ,
    Jakob N. Foerster
    ,
    J. Zico Kolter
  37. 37
    Conditional Bayesian Quadrature
    Zonghao Chen
    ,
    Masha Naslidnyk
    ,
    Arthur Gretton
    ,
    François-Xavier Briol
  38. 38
    Consistency Regularization for Domain Generalization with Logit Attribution Matching
    Han Gao
    ,
    Kaican Li
    ,
    Weiyan Xie
    ,
    Zhi Lin
    ,
    Yongxiang Huang
    ,
    Luning Wang
    ,
    Caleb Chen Cao
    ,
    Nevin L. Zhang
  39. 39
    ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-variable Context Encoding
    Denis A. Gudovskiy
    ,
    Tomoyuki Okuno
    ,
    Yohei Nakata
  40. 40
    Convergence Behavior of an Adversarial Weak Supervision Method
    Steven An
    ,
    Sanjoy Dasgupta
  41. 41
    Cooperative Meta-Learning with Gradient Augmentation
    Jongyun Shin
    ,
    Seungjin Han
    ,
    Jangho Kim
  42. 42
    Cost-Sensitive Uncertainty-Based Failure Recognition for Object Detection
    Moussa Kassem Sbeyti
    ,
    Michelle Karg
    ,
    Christian Wirth
    ,
    Nadja Klein
    ,
    Sahin Albayrak
  43. 43
    CSS: Contrastive Semantic Similarities for Uncertainty Quantification of LLMs
    Shuang Ao
    ,
    Stefan Rueger
    ,
    Advaith Siddharthan
  44. 44
    DataSP: A Differential All-to-All Shortest Path Algorithm for Learning Costs and Predicting Paths with Context
    Alan A. Lahoud
    ,
    Erik Schaffernicht
    ,
    Johannes A. Stork
  45. 45
    Decentralized Online Learning in General-Sum Stackelberg Games
    Yaolong Yu
    ,
    Haipeng Chen
  46. 46
    Decentralized Two-Sided Bandit Learning in Matching Market
    Yirui Zhang
    ,
    Zhixuan Fang
  47. 47
    Decision-Focused Evaluation of Worst-Case Distribution Shift
    Kevin Ren
    ,
    Yewon Byun
    ,
    Bryan Wilder
  48. 48
    Detecting critical treatment effect bias in small subgroups
    Piersilvio De Bartolomeis
    ,
    Javier Abad
    ,
    Konstantin Donhauser
    ,
    Fanny Yang
  49. 49
    Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect Estimation
    Yoichi Chikahara
    ,
    Kansei Ushiyama
  50. 50
    Differentially Private No-regret Exploration in Adversarial Markov Decision Processes
    Shaojie Bai
    ,
    Lanting Zeng
    ,
    Chengcheng Zhao
    ,
    Xiaoming Duan
    ,
    Mohammad Sadegh Talebi
    ,
    Peng Cheng
    ,
    Jiming Chen