AAAI 2024

2,864 papers

Learning Fair Policies for Multi-Stage Selection Problems from Observational Data

Zhuangzhuang Jia, Grani A. Hanasusanto, Phebe Vayanos, Weijun Xie

Stronger and Transferable Node Injection Attacks

Samyak Jain, Tanima Dutta

Personalization as a Shortcut for Few-Shot Backdoor Attack against Text-to-Image Diffusion Models

Yihao Huang, Felix Juefei-Xu, Qing Guo, Jie Zhang, Yutong Wu

On the Concept Trustworthiness in Concept Bottleneck Models

Qihan Huang, Jie Song, Jingwen Hu, Haofei Zhang, Yong Wang

Towards Efficient Verification of Quantized Neural Networks

Pei Huang, Haoze Wu, Yuting Yang, Ieva Daukantas, Min Wu

All but One: Surgical Concept Erasing with Model Preservation in Text-to-Image Diffusion Models

SeungHoo Hong, Juhun Lee, Simon S. Woo

Provable Robustness against a Union of L_0 Adversarial Attacks

Zayd Hammoudeh, Daniel Lowd

Omega-Regular Decision Processes

Ernst Moritz Hahn, Mateo Perez, Sven Schewe, Fabio Somenzi, Ashutosh Trivedi

Generative Model for Decision Trees

Riccardo Guidotti, Anna Monreale, Mattia Setzu, Giulia Volpi

π-Light: Programmatic Interpretable Reinforcement Learning for Resource-Limited Traffic Signal Control

Yin Gu, Kai Zhang, Qi Liu, Weibo Gao, Longfei Li

Balance Reward and Safety Optimization for Safe Reinforcement Learning: A Perspective of Gradient Manipulation

shangding gu, Bilgehan Sel, Yuhao Ding, Lu Wang, Qingwei Lin

Solving Non-rectangular Reward-Robust MDPs via Frequency Regularization

Uri Gadot, Esther Derman, Navdeep Kumar, Maxence Mohamed Elfatihi, Kfir Levy

CASE: Exploiting Intra-class Compactness and Inter-class Separability of Feature Embeddings for Out-of-Distribution Detection

Shuai Feng, Pengsheng Jin, Chongjun Wang

Invisible Backdoor Attack against 3D Point Cloud Classifier in Graph Spectral Domain

Linkun Fan, Fazhi He, Tongzhen Si, Wei Tang, Bing Li

A Simple and Yet Fairly Effective Defense for Graph Neural Networks

Sofiane Ennadir, Yassine Abbahaddou, Johannes F. Lutzeyer, Michalis Vazirgiannis, Henrik Boström

Automatically Testing Functional Properties of Code Translation Models

Hasan Ferit Eniser, Valentin Wüstholz, Maria Christakis

From Hope to Safety: Unlearning Biases of Deep Models via Gradient Penalization in Latent Space

Maximilian Dreyer, Frederik Pahde, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin

Trade-Offs in Fine-Tuned Diffusion Models between Accuracy and Interpretability

Mischa Dombrowski, Hadrien Reynaud, Johanna P. Müller, Matthew Baugh, Bernhard Kainz

P2BPO: Permeable Penalty Barrier-Based Policy Optimization for Safe RL

Sumanta Dey, Pallab Dasgupta, Soumyajit Dey

Robustness Verification of Multi-Class Tree Ensembles

Laurens Devos, Lorenzo Cascioli, Jesse Davis

Stability Analysis of Switched Linear Systems with Neural Lyapunov Functions

Virginie Debauche, Alec Edwards, Raphaël M. Jungers, Alessandro Abate

Find the Lady: Permutation and Re-synchronization of Deep Neural Networks

Carl De Sousa Trias, Mihai Petru Mitrea, Attilio Fiandrotti, Marco Cagnazzo, Sumanta Chaudhuri

TTTS: Tree Test Time Simulation for Enhancing Decision Tree Robustness against Adversarial Examples

Seffi Cohen, Ofir Arbili, Yisroel Mirsky, Lior Rokach

Conformal Prediction Regions for Time Series Using Linear Complementarity Programming

Matthew Cleaveland, Insup Lee, George J. Pappas, Lars Lindemann

Constrained Meta-Reinforcement Learning for Adaptable Safety Guarantee with Differentiable Convex Programming

Minjae Cho, Chuangchuang Sun

Truth Forest: Toward Multi-Scale Truthfulness in Large Language Models through Intervention without Tuning

Zhongzhi Chen, Xingwu Sun, Xianfeng Jiao, Fengzong Lian, Zhanhui Kang

Rethinking the Development of Large Language Models from the Causal Perspective: A Legal Text Prediction Case Study

Haotian Chen, Lingwei Zhang, Yiran Liu, Yang Yu

CCTR: Calibrating Trajectory Prediction for Uncertainty-Aware Motion Planning in Autonomous Driving

Chengtai Cao, Xinhong Chen, Jianping Wang, Qun Song, Rui Tan

Robust Uncertainty Quantification Using Conformalised Monte Carlo Prediction

Daniel Bethell, Simos Gerasimou, Radu Calinescu

Risk-Aware Continuous Control with Neural Contextual Bandits

Jose A. Ayala-Romero, Andres Garcia-Saavedra, Xavier Costa-Perez

On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods

Kasun Amarasinghe, Kit T. Rodolfa, Sérgio Jesus, Valerie Chen, Vladimir Balayan

A Framework for Data-Driven Explainability in Mathematical Optimization

Kevin-Martin Aigner, Marc Goerigk, Michael Hartisch, Frauke Liers, Arthur Miehlich

ImageCaptioner2: Image Captioner for Image Captioning Bias Amplification Assessment

Eslam Abdelrahman, Pengzhan Sun, Li Erran Li, Mohamed Elhoseiny

Two-Stage Evolutionary Reinforcement Learning for Enhancing Exploration and Exploitation

Qingling Zhu, Xiaoqiang Wu, Qiuzhen Lin, Wei-Neng Chen

How to Use the Metropolis Algorithm for Multi-Objective Optimization?

Weijie Zheng, Mingfeng Li, Renzhong Deng, Benjamin Doerr

Runtime Analysis of the SMS-EMOA for Many-Objective Optimization

Weijie Zheng, Benjamin Doerr

Jointly Improving the Sample and Communication Complexities in Decentralized Stochastic Minimax Optimization

Xuan Zhang, Gabriel Mancino-Ball, Necdet Serhat Aybat, Yangyang Xu

Threshold-Based Responsive Simulated Annealing for Directed Feedback Vertex Set Problem

Qingyun Zhang, Yuming Du, Zhouxing Su, Chu-Min Li, Junzhou Xu

Sample-and-Bound for Non-convex Optimization

Yaoguang Zhai, Zhizhen Qin, Sicun Gao

A Novel Skip Orthogonal List for Dynamic Optimal Transport Problem

Xiaoyang Xu, Hu Ding

Inertial Algorithm with Dry Fraction and Convolutional Sparse Coding for 3D Localization with Light Field Microscopy

Xiaofan Wang, Zhiyuan Deng, Changle Wang, Jinjia Wang

Improving Neural Network Generalization on Data-Limited Regression with Doubly-Robust Boosting

Hao Wang

COMBHelper: A Neural Approach to Reduce Search Space for Graph Combinatorial Problems

Hao Tian, Sourav Medya, Wei Ye

Learning Encodings for Constructive Neural Combinatorial Optimization Needs to Regret

Rui Sun, Zhi Zheng, Zhenkun Wang

Paths, Proofs, and Perfection: Developing a Human-Interpretable Proof System for Constrained Shortest Paths

Konstantin Sidorov, Gonçalo Homem de Almeida Correia, Mathijs de Weerdt, Emir Demirović

Accelerating Cutting-Plane Algorithms via Reinforcement Learning Surrogates

Kyle Mana, Fernando Acero, Stephen Mak, Parisa Zehtabi, Michael Cashmore

Towards Running Time Analysis of Interactive Multi-Objective Evolutionary Algorithms

Tianhao Lu, Chao Bian, Chao Qian

A Fast Exact Solver with Theoretical Analysis for the Maximum Edge-Weighted Clique Problem

LU LIU, Mingyu Xiao, Yi Zhou

Learning to Stop Cut Generation for Efficient Mixed-Integer Linear Programming

Haotian Ling, Zhihai Wang, Jie Wang

Rectangle Search: An Anytime Beam Search

Sofia Lemons, Wheeler Ruml, Rob Holte, Carlos Linares Lopez

Parallel Beam Search Algorithms for Domain-Independent Dynamic Programming

Ryo Kuroiwa, J. Christopher Beck

KD-Club: An Efficient Exact Algorithm with New Coloring-Based Upper Bound for the Maximum k-Defective Clique Problem

Mingming Jin, Jiongzhi Zheng, Kun He

Theoretical Aspects of Generating Instances with Unique Solutions: Pre-assignment Models for Unique Vertex Cover

Takashi Horiyama, Yasuaki Kobayashi, Hirotaka Ono, Kazuhisa Seto, Ryu Suzuki

Limited Query Graph Connectivity Test

Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung Nguyen

Efficient Constrained K-center Clustering with Background Knowledge

Longkun Guo, Chaoqi Jia, Kewen Liao, Zhigang Lu, Minhui Xue

Cumulative Regret Analysis of the Piyavskii–Shubert Algorithm and Its Variants for Global Optimization

Kaan Gokcesu, Hakan Gökcesu

Novelty vs. Potential Heuristics: A Comparison of Hardness Measures for Satisficing Planning

Simon Dold, Malte Helmert

Runtime Analysis of the (μ + 1) GA: Provable Speed-Ups from Strong Drift towards Diverse Populations

Benjamin Doerr, Aymen Echarghaoui, Mohammed Jamal, Martin S. Krejca

Traffic Flow Optimisation for Lifelong Multi-Agent Path Finding

Zhe Chen, Daniel Harabor, Jiaoyang Li, Peter J. Stuckey

Parameterized Approximation Algorithms for Sum of Radii Clustering and Variants

Xianrun Chen, Dachuan Xu, Yicheng Xu, Yong Zhang

Learning Ultrametric Trees for Optimal Transport Regression

Samantha Chen, Puoya Tabaghi, Yusu Wang

Sampling for Beyond-Worst-Case Online Ranking

Qingyun Chen, Sungjin Im, Benjamin Moseley, Chenyang Xu, Ruilong Zhang

An Interpretable Approach to the Solutions of High-Dimensional Partial Differential Equations

Lulu Cao, Yufei Liu, Zhenzhong Wang, Dejun Xu, Kai Ye

Delegation-Relegation for Boolean Matrix Factorization

Florent Avellaneda, Roger Villemaire

DOGE-Train: Discrete Optimization on GPU with End-to-End Training

Ahmed Abbas, Paul Swoboda

Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability Guarantees

Weijia Zhang, Chun Kai Ling, Xuanhui Zhang

Causal-Driven Skill Prerequisite Structure Discovery

Shenbao Yu, Yifeng Zeng, Fan Yang, Yinghui Pan

Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users

Hantao Yang, Xutong Liu, Zhiyong Wang, Hong Xie, John C. S. Lui

Neural Causal Abstractions

Kevin Xia, Elias Bareinboim

Linear-Time Algorithms for Front-Door Adjustment in Causal Graphs

Marcel Wienöbst, Benito van der Zander, Maciej Liśkiewicz

Inference and Learning in Dynamic Decision Networks Using Knowledge Compilation

Gabriele Venturato, Vincent Derkinderen, Pedro Zuidberg Dos Martires, Luc De Raedt

Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families

Russell Tsuchida, Cheng Soon Ong, Dino Sejdinovic

Bayesian Inference with Complex Knowledge Graph Evidence

Armin Toroghi, Scott Sanner

Learning Bayesian Network Classifiers to Minimize the Class Variable Parameters

Shouta Sugahara, Koya Kato, Maomi Ueno

A Fixed-Parameter Tractable Algorithm for Counting Markov Equivalence Classes with the Same Skeleton

Vidya Sagar Sharma

Causal Discovery from Poisson Branching Structural Causal Model Using High-Order Cumulant with Path Analysis

Jie Qiao, Yu Xiang, Zhengming Chen, Ruichu Cai, Zhifeng Hao

Identification of Causal Structure in the Presence of Missing Data with Additive Noise Model

Jie Qiao, Zhengming Chen, Jianhua Yu, Ruichu Cai, Zhifeng Hao

Root Cause Explanation of Outliers under Noisy Mechanisms

Phuoc Nguyen, Truyen Tran, Sunil Gupta, Thin Nguyen, Svetha Venkatesh

Colour Passing Revisited: Lifted Model Construction with Commutative Factors

Malte Luttermann, Tanya Braun, Ralf Möller, Marcel Gehrke

TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences

Yuequn Liu, Ruichu Cai, Wei Chen, Jie Qiao, Yuguang Yan

Solving Satisfiability Modulo Counting for Symbolic and Statistical AI Integration with Provable Guarantees

Jinzhao Li, Nan Jiang, Yexiang Xue

Unit Selection with Nonbinary Treatment and Effect

Ang Li, Judea Pearl

Probabilities of Causation with Nonbinary Treatment and Effect

Ang Li, Judea Pearl

Piecewise Linear Transformation – Propagating Aleatoric Uncertainty in Neural Networks

Thomas Krapf, Michael Hagn, Paul Miethaner, Alexander Schiller, Lucas Luttner

Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference

Dongyan (Lucy) Huo, Yudong Chen, Qiaomin Xie

Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach

Wen Huang, Xintao Wu

Learning Diffusions under Uncertainty

Hao Huang, Qian Yan, Keqi Han, Ting Gan, Jiawei Jiang

Uncertainty Quantification in Heterogeneous Treatment Effect Estimation with Gaussian-Process-Based Partially Linear Model

Shunsuke Horii, Yoichi Chikahara

Learning GAI-Decomposable Utility Models for Multiattribute Decision Making

Margot Herin, Patrice Perny, Nataliya Sokolovska

Identification for Tree-Shaped Structural Causal Models in Polynomial Time

Aaryan Gupta, Markus Bläser

Model Counting and Sampling via Semiring Extensions

Andreas Goral, Joachim Giesen, Mark Blacher, Christoph Staudt, Julien Klaus

Identifiability of Direct Effects from Summary Causal Graphs

Simon Ferreira, Charles K. Assaad

Generalized Bradley-Terry Models for Score Estimation from Paired Comparisons

Julien Fageot, Sadegh Farhadkhani, Lê-Nguyên Hoang, Oscar Villemaud

Probabilistic Offline Policy Ranking with Approximate Bayesian Computation

Longchao Da, Porter Jenkins, Trevor Schwantes, Jeffrey Dotson, Hua Wei

Direct Amortized Likelihood Ratio Estimation

Adam D. Cobb, Brian Matejek, Daniel Elenius, Anirban Roy, Susmit Jha

Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants

Wei Chen, Zhiyi Huang, Ruichu Cai, Zhifeng Hao, Kun Zhang

Minibatch Stochastic Three Points Method for Unconstrained Smooth Minimization

Soumia Boucherouite, Grigory Malinovsky, Peter Richtarik, El Houcine Bergou

Pandora’s Problem with Deadlines

Ben Berger, Tomer Ezra, Michal Feldman, Federico Fusco

The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank

Amitay Bar, Rotem Mulayoff, Tomer Michaeli, Ronen Talmon

Backward Responsibility in Transition Systems Using General Power Indices

Christel Baier, Roxane van den Bossche, Sascha Klüppelholz, Johannes Lehmann, Jakob Piribauer