Papers
938 papers found
Variational refinement for importance sampling using the forward Kullback-Leibler divergence
Ghassen Jerfel, Serena Wang, Clara Wong-Fannjiang et al.
Weighted model counting with conditional weights for Bayesian networks
Paulius Dilkas, Vaishak Belle
When is particle filtering efficient for planning in partially observed linear dynamical systems?
Simon S. Du, Wei Hu, Zhiyuan Li et al.
XOR-SGD: provable convex stochastic optimization for decision-making under uncertainty
Fan Ding, Yexiang Xue
99% of Worker-Master Communication in Distributed Optimization Is Not Needed
Konstantin Mishchenko, Filip Hanzely, Peter Richtarik
Active Learning of Conditional Mean Embeddings via Bayesian Optimisation
Sayak Ray Chowdhury, Rafael Oliveira, Fabio Ramos
Active Model Estimation in Markov Decision Processes
Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta et al.
Adapting Text Embeddings for Causal Inference
Victor Veitch, Dhanya Sridhar, David Blei
Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation
Marco Morucci, Vittorio Orlandi, Sudeepa Roy et al.
Adversarial Learning for 3D Matching
Wei Xing, Brian Ziebart
Amortized Bayesian Optimization over Discrete Spaces
Kevin Swersky, Yulia Rubanova, David Dohan et al.
Amortized Nesterov’s Momentum: A Robust Momentum and Its Application to Deep Learning
Kaiwen Zhou, Yanghua Jin, Qinghua Ding et al.
Amortized variance reduction for doubly stochastic objective
Ayman Boustati, Sattar Vakili, James Hensman et al.
Anchored Causal Inference in the Presence of Measurement Error
Basil Saeed, Anastasiya Belyaeva, Yuhao Wang et al.
An Interpretable and Sample Efficient Deep Kernel for Gaussian Process
Yijue Dai, Tianjian Zhang, Zhidi Lin et al.
A Practical Riemannian Algorithm for Computing Dominant Generalized Eigenspace
Zhiqiang Xu, Ping Li
A Simple Online Algorithm for Competing with Dynamic Comparators
Yu-Jie Zhang, Peng Zhao, Zhi-Hua Zhou
A SUPER* Algorithm to Optimize Paper Bidding in Peer Review
Tanner Fiez, Nihar Shah, Lillian Ratliff
Automated Dependence Plots
David Inouye, Liu Leqi, Joon Sik Kim et al.
Batch norm with entropic regularization turns deterministic autoencoders into generative models
Amur Ghose, Abdullah Rashwan, Pascal Poupart
Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation
Marko Jarvenpaa, Aki Vehtari, Pekka Marttinen
Bayesian Online Prediction of Change Points
Diego Agudelo-España, Sebastian Gomez-Gonzalez, Stefan Bauer et al.
Bounded Rationality in Las Vegas: Probabilistic Finite Automata Play Multi-Armed Bandits
Xinming Liu, Joseph Halpern
Bounding the expected run-time of nonconvex optimization with early stopping
Thomas Flynn, Kwangmin Yu, Abid Malik et al.
Causal screening in dynamical systems
Søren Wengel Mogensen