Papers
Learning to Discover Efficient Mathematical Identities
Wojciech Zaremba, Karol Kurach, Rob Fergus
Quantized Estimation of Gaussian Sequence Models in Euclidean Balls
Yuancheng Zhu, John Lafferty
Fairness in Multi-Agent Sequential Decision-Making
Chongjie Zhang, Julie A Shah
Learning to Search in Branch and Bound Algorithms
He He, Hal Daume III, Jason M Eisner
How transferable are features in deep neural networks?
Jason Yosinski, Jeff Clune, Yoshua Bengio et al.
The Blinded Bandit: Learning with Adaptive Feedback
Ofer Dekel, Elad Hazan, Tomer Koren
Analysis of Brain States from Multi-Region LFP Time-Series
Kyle R Ulrich, David E Carlson, Wenzhao Lian et al.
Time--Data Tradeoffs by Aggressive Smoothing
John J Bruer, Joel A Tropp, Volkan Cevher et al.
Grouping-Based Low-Rank Trajectory Completion and 3D Reconstruction
Katerina Fragkiadaki, Marta Salas, Pablo Arbelaez et al.
Optimal Teaching for Limited-Capacity Human Learners
Kaustubh R Patil, Xiaojin Zhu, Łukasz Kopeć et al.
Do Convnets Learn Correspondence?
Jonathan L Long, Ning Zhang, Trevor Darrell
Multitask learning meets tensor factorization: task imputation via convex optimization
Kishan Wimalawarne, Masashi Sugiyama, Ryota Tomioka
Exclusive Feature Learning on Arbitrary Structures via ℓ_1,2-norm
Deguang Kong, Ryohei Fujimaki, Ji Liu et al.
Robust Logistic Regression and Classification
Jiashi Feng, Huan Xu, Shie Mannor et al.
A Wild Bootstrap for Degenerate Kernel Tests
Kacper P Chwialkowski, Dino Sejdinovic, Arthur Gretton
Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP
Shinichi Nakajima, Issei Sato, Masashi Sugiyama et al.
Blossom Tree Graphical Models
Zhe Liu, John Lafferty
Zeta Hull Pursuits: Learning Nonconvex Data Hulls
Yuanjun Xiong, Wei Liu, Deli Zhao et al.
New Rules for Domain Independent Lifted MAP Inference
Happy Mittal, Prasoon Goyal, Vibhav G Gogate et al.
Scalable Non-linear Learning with Adaptive Polynomial Expansions
Alekh Agarwal, Alina Beygelzimer, Daniel J. Hsu et al.
Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space
Ian En-Hsu Yen, Ting-Wei Lin, Shou-De Lin et al.
A provable SVD-based algorithm for learning topics in dominant admixture corpus
Trapit Bansal, Chiranjib Bhattacharyya, Ravindran Kannan
Searching for Higgs Boson Decay Modes with Deep Learning
Peter J Sadowski, Daniel Whiteson, Pierre Baldi
Learning Generative Models with Visual Attention
Charlie Tang, Nitish Srivastava, Ruslan Salakhutdinov
Communication-Efficient Distributed Dual Coordinate Ascent
Martin Jaggi, Virginia Smith, Martin Takac et al.