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AISTATS 2024

A

International Conference on Artificial Intelligence and Statistics

Official site ↗
548
accepted papers
1,780
authors
May 2-4, 2024
dates
Spain
location

300 / 548 papers

  1. 1
    A 4-Approximation Algorithm for Min Max Correlation Clustering
    Holger S. G. Heidrich
    ,
    Jannik Irmai
    ,
    Bjoern Andres
  2. 2
    A Bayesian Learning Algorithm for Unknown Zero-sum Stochastic Games with an Arbitrary Opponent
    Mehdi Jafarnia-Jahromi
    ,
    Rahul Jain
    ,
    Ashutosh Nayyar
  3. 3
    A Cubic-regularized Policy Newton Algorithm for Reinforcement Learning
    Mizhaan Prajit Maniyar
    ,
    Prashanth L. A.
    ,
    Akash Mondal
    ,
    Shalabh Bhatnagar
  4. 4
    A Doubly Robust Approach to Sparse Reinforcement Learning
    Wonyoung Kim
    ,
    Garud Iyengar
    ,
    Assaf Zeevi
  5. 5
    A General Algorithm for Solving Rank-one Matrix Sensing
    Lianke Qin
    ,
    Zhao Song
    ,
    Ruizhe Zhang
  6. 6
    A General Theoretical Paradigm to Understand Learning from Human Preferences
    Mohammad Gheshlaghi Azar
    ,
    Zhaohan Daniel Guo
    ,
    Bilal Piot
    ,
    Rémi Munos
    ,
    Mark Rowland
    ,
    Michal Valko
    ,
    Daniele Calandriello
  7. 7
    A Greedy Approximation for k-Determinantal Point Processes
    Julia Grosse
    ,
    Rahel Fischer
    ,
    Roman Garnett
    ,
    Philipp Hennig
  8. 8
    A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization
    Mathieu Dagréou
    ,
    Thomas Moreau
    ,
    Samuel Vaiter
    ,
    Pierre Ablin
  9. 9
    A Neural Architecture Predictor based on GNN-Enhanced Transformer
    Xunzhi Xiang
    ,
    Kun Jing
    ,
    Jungang Xu
  10. 10
    A Primal-Dual-Critic Algorithm for Offline Constrained Reinforcement Learning
    Kihyuk Hong
    ,
    Yuhang Li
    ,
    Ambuj Tewari
  11. 11
    A Scalable Algorithm for Individually Fair k-Means Clustering
    MohammadHossein Bateni
    ,
    Vincent Cohen-Addad
    ,
    Alessandro Epasto
    ,
    Silvio Lattanzi
  12. 12
    A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport
    Tianyi Lin
    ,
    Marco Cuturi
    ,
    Michael I. Jordan
  13. 13
    A Unified Framework for Discovering Discrete Symmetries
    Pavan Karjol
    ,
    Rohan Kashyap
    ,
    Aditya Gopalan
    ,
    A. P. Prathosh
  14. 14
    A Unifying Variational Framework for Gaussian Process Motion Planning
    Lucas Cosier
    ,
    Rares Iordan
    ,
    Sicelukwanda N. T. Zwane
    ,
    Giovanni Franzese
    ,
    James T. Wilson
    ,
    Marc Peter Deisenroth
    ,
    Alexander Terenin
    ,
    Yasemin Bekiroglu
  15. 15
    A White-Box False Positive Adversarial Attack Method on Contrastive Loss Based Offline Handwritten Signature Verification Models
    Zhongliang Guo
    ,
    Weiye Li
    ,
    Yifei Qian
    ,
    Ognjen Arandjelovic
    ,
    Lei Fang
  16. 16
    A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity
    Zhihan Xiong
    ,
    Romain Camilleri
    ,
    Maryam Fazel
    ,
    Lalit Jain
    ,
    Kevin Jamieson
  17. 17
    A/B testing under Interference with Partial Network Information
    Shiv Shankar
    ,
    Ritwik Sinha
    ,
    Yash Chandak
    ,
    Saayan Mitra
    ,
    Madalina Fiterau
  18. 18
    Absence of spurious solutions far from ground truth: A low-rank analysis with high-order losses
    Ziye Ma
    ,
    Ying Chen
    ,
    Javad Lavaei
    ,
    Somayeh Sojoudi
  19. 19
    Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo
    Haoyang Zheng
    ,
    Wei Deng
    ,
    Christian Moya
    ,
    Guang Lin
  20. 20
    Acceleration and Implicit Regularization in Gaussian Phase Retrieval
    Tyler Maunu
    ,
    Martin Molina-Fructuoso
  21. 21
    Accuracy-Preserving Calibration via Statistical Modeling on Probability Simplex
    Yasushi Esaki
    ,
    Akihiro Nakamura
    ,
    Keisuke Kawano
    ,
    Ryoko Tokuhisa
    ,
    Takuro Kutsuna
  22. 22
    Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning
    Taeuk Jang
    ,
    Hongchang Gao
    ,
    Pengyi Shi
    ,
    Xiaoqian Wang
  23. 23
    Achieving Group Distributional Robustness and Minimax Group Fairness with Interpolating Classifiers
    Natalia Martínez
    ,
    Martín Bertrán
    ,
    Guillermo Sapiro
  24. 24
    Adaptive and non-adaptive minimax rates for weighted Laplacian-Eigenmap based nonparametric regression
    Zhaoyang Shi
    ,
    Krishna Balasubramanian
    ,
    Wolfgang Polonik
  25. 25
    Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach
    Masaki Adachi
    ,
    Satoshi Hayakawa
    ,
    Martin Jørgensen
    ,
    Xingchen Wan
    ,
    Vu Nguyen
    ,
    Harald Oberhauser
    ,
    Michael A. Osborne
  26. 26
    Adaptive Compression in Federated Learning via Side Information
    Berivan Isik
    ,
    Francesco Pase
    ,
    Deniz Gündüz
    ,
    Sanmi Koyejo
    ,
    Tsachy Weissman
    ,
    Michele Zorzi
  27. 27
    Adaptive Discretization for Event PredicTion (ADEPT)
    Jimmy Hickey
    ,
    Ricardo Henao
    ,
    Daniel Wojdyla
    ,
    Michael J. Pencina
    ,
    Matthew Engelhard
  28. 28
    Adaptive Experiment Design with Synthetic Controls
    Alihan Hüyük
    ,
    Zhaozhi Qian
    ,
    Mihaela van der Schaar
  29. 29
    Adaptive Federated Minimax Optimization with Lower Complexities
    Feihu Huang
    ,
    Xinrui Wang
    ,
    Junyi Li
    ,
    Songcan Chen
  30. 30
    Adaptive importance sampling for heavy-tailed distributions via α-divergence minimization
    Thomas Guilmeau
    ,
    Nicola Branchini
    ,
    Emilie Chouzenoux
    ,
    Victor Elvira
  31. 31
    Adaptive Parametric Prototype Learning for Cross-Domain Few-Shot Classification
    Marzi Heidari
    ,
    Abdullah Alchihabi
    ,
    Qing En
    ,
    Yuhong Guo
  32. 32
    Adaptive Quasi-Newton and Anderson Acceleration Framework with Explicit Global (Accelerated) Convergence Rates
    Damien Scieur
  33. 33
    Adaptivity of Diffusion Models to Manifold Structures
    Rong Tang
    ,
    Yun Yang
  34. 34
    Agnostic Multi-Robust Learning using ERM
    Saba Ahmadi
    ,
    Avrim Blum
    ,
    Omar Montasser
    ,
    Kevin M. Stangl
  35. 35
    ALAS: Active Learning for Autoconversion Rates Prediction from Satellite Data
    Maria C. Novitasari
    ,
    Johannes Quaas
    ,
    Miguel Rodrigues
  36. 36
    An Analytic Solution to Covariance Propagation in Neural Networks
    Oren Wright
    ,
    Yorie Nakahira
    ,
    José M. F. Moura
  37. 37
    An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization
    Lesi Chen
    ,
    Haishan Ye
    ,
    Luo Luo
  38. 38
    An Impossibility Theorem for Node Embedding
    T. Mitchell Roddenberry
    ,
    Yu Zhu
    ,
    Santiago Segarra
  39. 39
    An Improved Algorithm for Learning Drifting Discrete Distributions
    Alessio Mazzetto
  40. 40
    An Online Bootstrap for Time Series
    Nicolai Palm
    ,
    Thomas Nagler
  41. 41
    Analysis of Kernel Mirror Prox for Measure Optimization
    Pavel E. Dvurechensky
    ,
    Jia-Jie Zhu
  42. 42
    Analysis of Privacy Leakage in Federated Large Language Models
    Minh N. Vu
    ,
    Truc D. T. Nguyen
    ,
    Tre' R. Jeter
    ,
    My T. Thai
  43. 43
    Analysis of Using Sigmoid Loss for Contrastive Learning
    Chungpa Lee
    ,
    Joonhwan Chang
    ,
    Jy-yong Sohn
  44. 44
    Analyzing Explainer Robustness via Probabilistic Lipschitzness of Prediction Functions
    Zulqarnain Khan
    ,
    Davin Hill
    ,
    Aria Masoomi
    ,
    Joshua T. Bone
    ,
    Jennifer G. Dy
  45. 45
    Any-dimensional equivariant neural networks
    Eitan Levin
    ,
    Mateo Díaz
  46. 46
    Anytime-Constrained Reinforcement Learning
    Jeremy McMahan
    ,
    Xiaojin Zhu
  47. 47
    Approximate Bayesian Class-Conditional Models under Continuous Representation Shift
    Thomas L. Lee
    ,
    Amos J. Storkey
  48. 48
    Approximate Control for Continuous-Time POMDPs
    Yannick Eich
    ,
    Bastian Alt
    ,
    Heinz Koeppl
  49. 49
    Approximate Leave-one-out Cross Validation for Regression with ℓ1 Regularizers
    Arnab Auddy
    ,
    Haolin Zou
    ,
    Kamiar Rahnama Rad
    ,
    Arian Maleki
  50. 50
    AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms
    Rustem Islamov
    ,
    Mher Safaryan
    ,
    Dan Alistarh