Papers
8,340 papers found
DR-ABC: Approximate Bayesian Computation with Kernel-Based Distribution Regression
Jovana Mitrovic, Dino Sejdinovic, Yee-Whye Teh
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Yarin Gal, Zoubin Ghahramani
Dropout distillation
Samuel Rota Bulò, Lorenzo Porzi, Peter Kontschieder
Dueling Network Architectures for Deep Reinforcement Learning
Ziyu Wang, Tom Schaul, Matteo Hessel et al.
Dynamic Capacity Networks
Amjad Almahairi, Nicolas Ballas, Tim Cooijmans et al.
Dynamic Memory Networks for Visual and Textual Question Answering
Caiming Xiong, Stephen Merity, Richard Socher
Early and Reliable Event Detection Using Proximity Space Representation
Maxime Sangnier, Jerome Gauthier, Alain Rakotomamonjy
Efficient Algorithms for Adversarial Contextual Learning
Vasilis Syrgkanis, Akshay Krishnamurthy, Robert Schapire
Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis
Rong Ge, Chi Jin, Sham et al.
Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity
Quanming Yao, James Kwok
Efficient Multi-Instance Learning for Activity Recognition from Time Series Data Using an Auto-Regressive Hidden Markov Model
Xinze Guan, Raviv Raich, Weng-Keen Wong
Efficient Private Empirical Risk Minimization for High-dimensional Learning
Shiva Prasad Kasiviswanathan, Hongxia Jin
Energetic Natural Gradient Descent
Philip Thomas, Bruno Castro Silva, Christoph Dann et al.
Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling
Christopher De Sa, Chris Re, Kunle Olukotun
Epigraph projections for fast general convex programming
Po-Wei Wang, Matt Wytock, Zico Kolter
Estimating Accuracy from Unlabeled Data: A Bayesian Approach
Emmanouil Antonios Platanios, Avinava Dubey, Tom Mitchell
Estimating Cosmological Parameters from the Dark Matter Distribution
Siamak Ravanbakhsh, Junier Oliva, Sebastian Fromenteau et al.
Estimating Maximum Expected Value through Gaussian Approximation
Carlo D’Eramo, Marcello Restelli, Alessandro Nuara
Estimating Structured Vector Autoregressive Models
Igor Melnyk, Arindam Banerjee
Estimation from Indirect Supervision with Linear Moments
Aditi Raghunathan, Roy Frostig, John Duchi et al.
Evasion and Hardening of Tree Ensemble Classifiers
Alex Kantchelian, J. D. Tygar, Anthony Joseph
Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling
Zeyuan Allen-Zhu, Zheng Qu, Peter Richtarik et al.
Exact Exponent in Optimal Rates for Crowdsourcing
Chao Gao, Yu Lu, Dengyong Zhou
Experimental Design on a Budget for Sparse Linear Models and Applications
Sathya Narayanan Ravi, Vamsi Ithapu, Sterling Johnson et al.
Exploiting Cyclic Symmetry in Convolutional Neural Networks
Sander Dieleman, Jeffrey De Fauw, Koray Kavukcuoglu