Papers
Adaptive Proximal Average Based Variance Reducing Stochastic Methods for Optimization with Composite Regularization
Jingchang Liu, Linli Xu, Junliang Guo et al.
RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets
Liping Li, Wei Xu, Tianyi Chen et al.
A Recursive Algorithm for Projected Model Counting
Jean-Marie Lagniez, Pierre Marquis
Asynchronous Delay-Aware Accelerated Proximal Coordinate Descent for Nonconvex Nonsmooth Problems
Ehsan Kazemi, Liqiang Wang
Separator-Based Pruned Dynamic Programming for Steiner Tree
Yoichi Iwata, Takuto Shigemura
Abduction-Based Explanations for Machine Learning Models
Alexey Ignatiev, Nina Narodytska, Joao Marques-Silva
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization
Feihu Huang, Bin Gu, Zhouyuan Huo et al.
Constraint-Based Sequential Pattern Mining with Decision Diagrams
Amin Hosseininasab, Willem-Jan van Hoeve, Andre A. Cire
Stochastic Submodular Maximization with Performance-Dependent Item Costs
Takuro Fukunaga, Takuya Konishi, Sumio Fujita et al.
Solving Integer Quadratic Programming via Explicit and Structural Restrictions
Eduard Eiben, Robert Ganian, Dusan Knop et al.
A Nonconvex Projection Method for Robust PCA
Aritra Dutta, Filip Hanzely, Peter Richtàrik
On Geometric Alignment in Low Doubling Dimension
Hu Ding, Mingquan Ye
Model-Based Diagnosis of Hybrid Systems Using Satisfiability Modulo Theory
Alexander Diedrich, Alexander Maier, Oliver Niggemann
Improving Optimization Bounds Using Machine Learning: Decision Diagrams Meet Deep Reinforcement Learning
Quentin Cappart, Emmanuel Goutierre, David Bergman et al.
A SAT+CAS Approach to Finding Good Matrices: New Examples and Counterexamples
Curtis Bright, Dragomir Ž. Ðoković, Ilias Kotsireas et al.
Clairvoyant Restarts in Branch-and-Bound Search Using Online Tree-Size Estimation
Daniel Anderson, Gregor Hendel, Pierre Le Bodic et al.
Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making
Sina Aghaei, Mohammad Javad Azizi, Phebe Vayanos
A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data
Chuxu Zhang, Dongjin Song, Yuncong Chen et al.
Deep Reinforcement Learning for Green Security Games with Real-Time Information
Yufei Wang, Zheyuan Ryan Shi, Lantao Yu et al.
A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems
Ling Pan, Qingpeng Cai, Zhixuan Fang et al.
Interpretable Predictive Modeling for Climate Variables with Weighted Lasso
Sijie He, Xinyan Li, Vidyashankar Sivakumar et al.
Deep Bayesian Optimization on Attributed Graphs
Jiaxu Cui, Bo Yang, Xia Hu
Modelling Autobiographical Memory Loss across Life Span
Di Wang, Ah-Hwee Tan, Chunyan Miao et al.
Simulation-Based Approach to Efficient Commonsense Reasoning in Very Large Knowledge Bases
Abhishek Sharma, Keith M. Goolsbey
Scalable Recollections for Continual Lifelong Learning
Matthew Riemer, Tim Klinger, Djallel Bouneffouf et al.