Papers
4,025 papers found
Benefits from Superposed Hawkes Processes
Hongteng Xu, Dixin Luo, Xu Chen et al.
Best arm identification in multi-armed bandits with delayed feedback
Aditya Grover, Todor Markov, Peter Attia et al.
Boosting Variational Inference: an Optimization Perspective
Francesco Locatello, Rajiv Khanna, Joydeep Ghosh et al.
Bootstrapping EM via Power EM and Convergence in the Naive Bayes Model
Costis Daskalakis, Christos Tzamos, Manolis Zampetakis
Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and k-means
Dennis Forster, Jörg Lücke
Catalyst for Gradient-based Nonconvex Optimization
Courtney Paquette, Hongzhou Lin, Dmitriy Drusvyatskiy et al.
Cause-Effect Inference by Comparing Regression Errors
Patrick Bloebaum, Dominik Janzing, Takashi Washio et al.
Cheap Checking for Cloud Computing: Statistical Analysis via Annotated Data Streams
Chris Hickey, Graham Cormode
Combinatorial Penalties: Which structures are preserved by convex relaxations?
Marwa El Halabi, Francis Bach, Volkan Cevher
Combinatorial Preconditioners for Proximal Algorithms on Graphs
Thomas Möllenhoff, Zhenzhang Ye, Tao Wu et al.
Combinatorial Semi-Bandits with Knapsacks
Karthik Abinav Sankararaman, Aleksandrs Slivkins
Communication-Avoiding Optimization Methods for Distributed Massive-Scale Sparse Inverse Covariance Estimation
Penporn Koanantakool, Alnur Ali, Ariful Azad et al.
Community Detection in Hypergraphs: Optimal Statistical Limit and Efficient Algorithms
I Chien, Chung-Yi Lin, I-Hsiang Wang
Comparison Based Learning from Weak Oracles
Ehsan Kazemi, Lin Chen, Sanjoy Dasgupta et al.
Competing with Automata-based Expert Sequences
Mehryar Mohri, Scott Yang
Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap
Aryan Mokhtari, Hamed Hassani, Amin Karbasi
Contextual Bandits with Stochastic Experts
Rajat Sen, Karthikeyan Shanmugam, Sanjay Shakkottai
Convergence diagnostics for stochastic gradient descent with constant learning rate
Jerry Chee, Panos Toulis
Convergence of Value Aggregation for Imitation Learning
Ching-An Cheng, Byron Boots
Convex Optimization over Intersection of Simple Sets: improved Convergence Rate Guarantees via an Exact Penalty Approach
Achintya Kundu, Francis Bach, Chiranjib Bhattacharya
Crowdclustering with Partition Labels
Junxiang Chen, Yale Chang, Peter Castaldi et al.
Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control
Sanket Kamthe, Marc Deisenroth
Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programs
Lawrence Murray, Daniel Lundén, Jan Kudlicka et al.
Derivative Free Optimization Via Repeated Classification
Tatsunori Hashimoto, Steve Yadlowsky, John Duchi