Papers
Contaminated Multivariate Time-Series Anomaly Detection with Spatio-Temporal Graph Conditional Diffusion Models
Thi Kieu Khanh Ho, Narges Armanfard
LoSAM: Local Search in Additive Noise Models with Mixed Mechanisms and General Noise for Global Causal Discovery
Sujai Hiremath, Promit Ghosal, Kyra Gan
SPvR: Structured Pruning via Ranking
Atif Hassan, Jiaul H. Paik, Swanand Khare
RCAP: Robust, Class-Aware, Probabilistic Dynamic Dataset Pruning
Atif Hassan, Swanand Khare, Jiaul H. Paik
Quantum Speedups for Bayesian Network Structure Learning
Juha Harviainen, Kseniya Rychkova, Mikko Koivisto
Conformal Prediction without Nonconformity Scores
Jonas Hanselle, Alireza Javanmardi, Tobias Florin Oberkofler et al.
Contrast-CAT: Contrasting Activations for Enhanced Interpretability in Transformer-based Text Classifiers
Sungmin Han, Jeonghyun Lee, Sangkyun Lee
Learning Algorithms for Multiple Instance Regression
Aaryan Gupta, Rishi Saket
On the Privacy Risks of Spiking Neural Networks: A Membership Inference Analysis
Junyi Guan, Abhijith Sharma, Chong Tian et al.
Guaranteed Prediction Sets for Functional Surrogate Models
Ander Gray, Vignesh Gopakumar, Sylvain Rousseau et al.
Efficient Algorithms for Logistic Contextual Slate Bandits with Bandit Feedback
Tanmay Goyal, Gaurav Sinha
Optimal Zero-shot Regret Minimization for Selective Classification with Out-of-Distribution Detection
Eduardo Dadalto Câmara Gomes, Marco Romanelli
Statistical Significance of Feature Importance Rankings
Jeremy Goldwasser, Giles Hooker
Nonlinear Causal Discovery for Grouped Data
Konstantin Göbler, Tobias Windisch, Mathias Drton
A 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 et al.
Order-Optimal Global Convergence for Actor-Critic with General Policy and Neural Critic Parametrization
Swetha Ganesh, Jiayu Chen, Washim Uddin Mondal et al.
Partial-Label Learning with Conformal Candidate Cleaning
Tobias Fuchs, Florian Kalinke
Improved Uncertainty Quantification in Physics-Informed Neural Networks Using Error Bounds and Solution Bundles
Pablo Flores, Olga Graf, Pavlos Protopapas et al.
Generalised Probabilistic Modelling and Improved Uncertainty Estimation in Comparative LLM-as-a-judge
Yassir Fathullah, Mark Gales
Proximal Interacting Particle Langevin Algorithms
Paula Cordero Encinar, Francesca Romana Crucinio, Omer Deniz Akyildiz
Mixup Regularization: A Probabilistic Perspective
Yousef El-Laham, Niccolo Dalmasso, Svitlana Vyetrenko et al.
Toward Universal Laws of Outlier Propagation
Aram Ebtekar, Yuhao Wang, Dominik Janzing
Learning Causal Response Representations through Direct Effect Analysis
Homer Durand, Gherardo Varando, Gustau Camps-Valls
Probabilistic Semantics Guided Discovery of Approximate Functional Dependencies
Liang Duan, Xinran Wu, Xinhui Li et al.