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Theory

4950 directly classified papers

Papers per year

Papers

Full-Capacity Unitary Recurrent Neural Networks NIPS 2016
Guarding against Spurious Discoveries in High Dimensions JMLR 2016
On the Recursive Teaching Dimension of VC Classes NIPS 2016
Spectral M-estimation with Applications to Hidden Markov Models AISTATS 2016
Simple and Scalable Constrained Clustering: a Generalized Spectral Method AISTATS 2016
Better call Saul: Flexible Programming for Learning and Inference in NLP COLING 2016
Solving Marginal MAP Problems with NP Oracles and Parity Constraints NIPS 2016
Sign rank versus VC dimension COLT 2016
Convolutional Rectifier Networks as Generalized Tensor Decompositions ICML 2016
A Bounded p-norm Approximation of Max-Convolution for Sub-Quadratic Bayesian Inference on Additive Factors JMLR 2016
Complexity Theoretic Limitations on Learning DNF’s COLT 2016
The Power of Depth for Feedforward Neural Networks COLT 2016
Open Problem: Property Elicitation and Elicitation Complexity COLT 2016
Set-labelled filters and sensor transformations RSS 2016
On the Expressive Power of Deep Learning: A Tensor Analysis COLT 2016
The Effect of Combination Functions on the Complexity of Relational Bayesian Networks PGM 2016
How Neural Network Depth Compensates for HMM Conditional Independence Assumptions in DNN-HMM Acoustic Models INTERSPEECH 2016
Multiple-Instance Learning from Distributions JMLR 2016
Near Optimal Behavior via Approximate State Abstraction ICML 2016
Fast Collaborative Filtering from Implicit Feedback with Provable Guarantees ACML 2016
On the Statistical Limits of Convex Relaxations ICML 2016
Relationship between PreTraining and Maximum Likelihood Estimation in Deep Boltzmann Machines AISTATS 2016
Open Problem: Second order regret bounds based on scaling time COLT 2016
The Parameterized Complexity of Approximate Inference in Bayesian Networks PGM 2016
A Characterization of Linkage-Based Hierarchical Clustering JMLR 2016