Papers
938 papers found
Doubly non-central beta matrix factorization for DNA methylation data
Aaron Schein, Anjali Nagulpally, Hanna Wallach et al.
Dynamic visualization for L1 fusion convex clustering in near-linear time
Bingyuan Zhang, Jie Chen, Yoshikazu Terada
Efficient debiased evidence estimation by multilevel Monte Carlo sampling
Kei Ishikawa, Takashi Goda
Efficient greedy coordinate descent via variable partitioning
Huang Fang, Guanhua Fang, Tan Yu et al.
Efficient online inference for nonparametric mixture models
Rylan Schaeffer, Blake Bordelon, Mikail Khona et al.
Enabling long-range exploration in minimization of multimodal functions
Jiaxin Zhang, Hoang Tran, Dan Lu et al.
Entropic Inequality Constraints from e-separation Relations in Directed Acyclic Graphs with Hidden Variables
Noam Finkelstein, Beata Zjawin, Elie Wolfe et al.
Escaping from zero gradient: Revisiting action-constrained reinforcement learning via Frank-Wolfe policy optimization
Jyun-Li Lin, Wei Hung, Shang-Hsuan Yang et al.
Estimating treatment effects with observed confounders and mediators
Shantanu Gupta, Zachary C. Lipton, David Childers
Exact and approximate hierarchical clustering using A*
Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath et al.
Explaining fast improvement in online imitation learning
Xinyan Yan, Byron Boots, Ching-An Cheng
Explicit pairwise factorized graph neural network for semi-supervised node classification
Yu Wang, Yuesong Shen, Daniel Cremers
Exploring the loss landscape in neural architecture search
Colin White, Sam Nolen, Yash Savani
Extendability of causal graphical models: Algorithms and computational complexity
Marcel Wienöbst, Max Bannach, Maciej Liśkiewicz
Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling
Difan Zou, Pan Xu, Quanquan Gu
Faster lifting for two-variable logic using cell graphs
Timothy van Bremen, Ondřej Kuželka
Featurized density ratio estimation
Kristy Choi, Madeline Liao, Stefano Ermon
Federated stochastic gradient Langevin dynamics
Khaoula el Mekkaoui, Diego Mesquita, Paul Blomstedt et al.
Finite-time theory for momentum Q-learning
Weng Bowen, Xiong Huaqing, Zhao Lin et al.
FlexAE: flexibly learning latent priors for wasserstein auto-encoders
Arnab Kumar Mondal, Himanshu Asnani, Parag Singla et al.
Formal verification of neural networks for safety-critical tasks in deep reinforcement learning
Davide Corsi, Enrico Marchesini, Alessandro Farinelli
Gaussian process nowcasting: application to COVID-19 mortality reporting
Iwona Hawryluk, Henrique Hoeltgebaum, Swapnil Mishra et al.
Generalization error bounds for deep unfolding RNNs
Boris Joukovsky, Tanmoy Mukherjee, Huynh Van Luong et al.
Generalized parametric path problems
Kshitij Gajjar, Girish Varma, Prerona Chatterjee et al.
Generating adversarial examples with graph neural networks
Florian Jaeckle, M. Pawan Kumar