Papers
Random Fourier Features For Operator-Valued Kernels
Romain Brault, Markus Heinonen, Florence Buc
Linearized Alternating Direction Method of Multipliers for Constrained Nonconvex Regularized Optimization
Linbo Qiao, Bofeng Zhang, Jinshu Su et al.
Localized Multiple Kernel Learning—A Convex Approach
Yunwen Lei, Alexander Binder, Urun Dogan et al.
Cost Sensitive Online Multiple Kernel Classification
Doyen Sahoo, Steven Hoi, Peilin Zhao
Multiple Kernel Learning with Data Augmentation
Khanh Nguyen, Trung Le, Vu Nguyen et al.
Enhancing Topic Modeling on Short Texts with Crowdsourcing
Xiaoyan Yang, Shanshan Ying, Wenzhe Yu et al.
Long Short-term Memory Network over Rhetorical Structure Theory for Sentence-level Sentiment Analysis
Xianghua Fu, Wangwang Liu, Yingying Xu et al.
Non-Linear Smoothed Transductive Network Embedding with Text Information
Weizheng Chen, Xia Zhang, Jinpeng Wang et al.
Parameter-Free Convex Learning through Coin Betting
Francesco Orabona, Dávid Pál
TPOT: A Tree-based Pipeline Optimization Tool for Automating Machine Learning
Randal S. Olson, Jason H. Moore
Towards Automatically-Tuned Neural Networks
Hector Mendoza, Aaron Klein, Matthias Feurer et al.
Adapting Multicomponent Predictive Systems using Hybrid Adaptation Strategies with Auto-WEKA in Process Industry
Manuel Martin Salvador, Marcin Budka, Bogdan Gabrys
Bayesian optimization for automated model selection
Gustavo Malkomes, Chip Schaff, Roman Garnett
Scalable Structure Discovery in Regression using Gaussian Processes
Hyunjik Kim, Yee Whye Teh
A Brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning Without Human Intervention
Isabelle Guyon, Imad Chaabane, Hugo Jair Escalante et al.
A Strategy for Ranking Optimization Methods using Multiple Criteria
Ian Dewancker, Michael McCourt, Scott Clark et al.
Effect of Incomplete Meta-dataset on Average Ranking Method
Salisu Mamman Abdulrahman, Pavel Brazdil
Minimizing Quadratic Functions in Constant Time
Kohei Hayashi, Yuichi Yoshida
Natural-Parameter Networks: A Class of Probabilistic Neural Networks
Hao Wang, Xingjian SHI, Dit-Yan Yeung
Generating Long-term Trajectories Using Deep Hierarchical Networks
Stephan Zheng, Yisong Yue, Jennifer Hobbs
Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition
Ahmed M. Alaa, Mihaela van der Schaar
General Tensor Spectral Co-clustering for Higher-Order Data
Tao Wu, Austin R Benson, David F Gleich
Optimal Learning for Multi-pass Stochastic Gradient Methods
Junhong Lin, Lorenzo Rosasco
Visual Question Answering with Question Representation Update (QRU)
Ruiyu Li, Jiaya Jia
Dueling Bandits: Beyond Condorcet Winners to General Tournament Solutions
Siddartha Y. Ramamohan, Arun Rajkumar, Shivani Agarwal et al.