Papers
COS-DPO: Conditioned One-Shot Multi-Objective Fine-Tuning Framework
Yinuo Ren, Tesi Xiao, Michael Shavlovsky et al.
FeDCM: Federated Learning of Deep Causal Generative Models
Md Musfiqur Rahman, Murat Kocaoglu
Enhanced Equilibria-Solving via Private Information Pre-Branch Structure in Adversarial Team Games
Chen Qiu, Haobo Fu, Kai Li et al.
Multi-Label Bayesian Active Learning with Inter-Label Relationships
Yuanyuan Qi, Jueqing Lu, Xiaohao Yang et al.
A Trust-Region Method for Graphical Stein Variational Inference
Liam Pavlovic, David M Rosen
Probabilistic Graph Circuits: Deep Generative Models for Tractable Probabilistic Inference over Graphs
Milan Papez, Martin Rektoris, Vaclav Smidl et al.
Exploring Exploration in Bayesian Optimization
Leonard Papenmeier, Nuojin Cheng, Stephen Becker et al.
Correlated Quantization for Faster Nonconvex Distributed Optimization
Andrei Panferov, Yury Demidovich, Ahmad Rammal et al.
Concept Forgetting via Label Annealing
Subhodip Panda, Ananda Theertha Suresh, Atri Guha et al.
An Information-theoretic Perspective of Hierarchical Clustering on Graphs
Yicheng Pan, Bingchen Fan, Pengyu Long et al.
Do Vendi Scores Converge with Finite Samples? Truncated Vendi Score for Finite-Sample Convergence Guarantees
Azim Ospanov, Farzan Farnia
Discriminative ordering through ensemble consensus
Louis Ohl, Fredrik Lindsten
i$^2$VAE: Interest Information Augmentation with Variational Regularizers for Cross-Domain Sequential Recommendation
Xuying Ning, Wujiang Xu, Tianxin Wei et al.
Bayesian Optimization over Bounded Domains with the Beta Product Kernel
Huy Hoang Nguyen, Han Zhou, Matthew B. Blaschko et al.
Stochastic Embeddings : A Probabilistic and Geometric Analysis of Out-of-Distribution Behavior
Anthony Nguyen, Emanuel Aldea, Sylvie Le Hégarat-Mascle et al.
Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization
Hai Dai Nguyen, Hiroshi Mamitsuka, Atsuyoshi Nakamura
Temperature Optimization for Bayesian Deep Learning
Kenyon Ng, Chris van der Heide, Liam Hodgkinson et al.
Relational Causal Discovery with Latent Confounders
Matteo Negro, Andrea Piras, Ragib Ahsan et al.
When Extragradient Meets PAGE: Bridging Two Giants to Boost Variational Inequalities
Gleb Molodtsov, Valery Parfenov, Egor Petrov et al.
SpinSVAR: Estimating Structural Vector Autoregression Assuming Sparse Input
Panagiotis Misiakos, Markus Püschel
ODD: Overlap-aware Estimation of Model Performance under Distribution Shift
Aayush Mishra, Anqi Liu
A Quantum Information Theoretic Approach to Tractable Probabilistic Models
Pedro Zuidberg Dos Martires
Improved Variational Inference in Discrete VAEs using Error Correcting Codes
María Martínez-García, Grace Villacrés, David Mitchell et al.