Papers
DEAP: Evolutionary Algorithms Made Easy
Félix-Antoine Fortin, François-Michel De Rainville, Marc-André Gardner et al.
Deep Boltzmann Machines as Feed-Forward Hierarchies
Gregoire Montavon, Mikio Braun, Klaus-Robert Muller
Deep Learning Made Easier by Linear Transformations in Perceptrons
Tapani Raiko, Harri Valpola, Yann Lecun
Deep Learning of Invariant Features via Simulated Fixations in Video
Will Zou, Shenghuo Zhu, Kai Yu et al.
Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images
Dan Ciresan, Alessandro Giusti, Luca M. Gambardella et al.
Deep Representations and Codes for Image Auto-Annotation
Ryan Kiros, Csaba Szepesvári
Deep Spatio-Temporal Architectures and Learning for Protein Structure Prediction
Pietro D. Lena, Ken Nagata, Pierre F. Baldi
Delay Compensation with Dynamical Synapses
Chi Fung, K. Wong, Si Wu
Density-Difference Estimation
Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki et al.
Density Propagation and Improved Bounds on the Partition Function
Stefano Ermon, Ashish Sabharwal, Bart Selman et al.
Detecting Network Cliques with Radon Basis Pursuit
Xiaoye Jiang, Yuan Yao, Han Liu et al.
Deterministic Annealing for Semi-Supervised Structured Output Learning
Paramveer Dhillon, Sathiya Keerthi, Kedar Bellare et al.
Development of a Testbed for Robotic Neuromuscular Controllers
Alexander Schepelmann, Hartmut Geyer, Michael Taylor
Differentially Private Online Learning
Prateek Jain, Pravesh Kothari, Abhradeep Thakurta
Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification
Yung-kyun Noh, Frank Park, Daniel D. Lee
Dimensionality Dependent PAC-Bayes Margin Bound
Chi Jin, Liwei Wang
Dip-means: an incremental clustering method for estimating the number of clusters
Argyris Kalogeratos, Aristidis Likas
Discriminative Hierarchical Part-based Models for Human Parsing and Action Recognition
Yang Wang, Duan Tran, Zicheng Liao et al.
Discriminative Learning of Sum-Product Networks
Robert Gens, Pedro Domingos
Discriminatively Trained Sparse Code Gradients for Contour Detection
Ren Xiaofeng, Liefeng Bo
Discriminative Mixtures of Sparse Latent Fields for Risk Management
Felix Agakov, Peter Orchard, Amos Storkey
Distance Metric Learning with Eigenvalue Optimization
Yiming Ying, Peng Li
Distributed Approximation of Joint Measurement Distributions Using Mixtures of Gaussians
Brian Julian, Stephen Smith, Daniela Rus
Distributed Learning, Communication Complexity and Privacy
Maria Florina Balcan, Avrim Blum, Shai Fine et al.