conftrace_
← Optimization & Theory
Machine Learning › Optimization & Theory ›

Statistical Learning

4,117 papers

Papers per year

9
62
100
382
192
'05
'10
'15
'20
'25

Papers

Unifying Non-Maximum Likelihood Learning Objectives with Minimum KL Contraction NIPS 2011
Efficient inference in matrix-variate Gaussian models with \iid observation noise NIPS 2011
Confidence Sets for Network Structure NIPS 2011
Structural equations and divisive normalization for energy-dependent component analysis NIPS 2011
High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity NIPS 2011
Statistical Tests for Optimization Efficiency NIPS 2011
Statistical Performance of Convex Tensor Decomposition NIPS 2011
Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs NIPS 2011
Noise Thresholds for Spectral Clustering NIPS 2011
A blind sparse deconvolution method for neural spike identification NIPS 2011
Universal low-rank matrix recovery from Pauli measurements NIPS 2011
On the accuracy of l1-filtering of signals with block-sparse structure NIPS 2011
Learning with the weighted trace-norm under arbitrary sampling distributions NIPS 2011
Demixed Principal Component Analysis NIPS 2011
Differentially Private M-Estimators NIPS 2011
Sparse Estimation with Structured Dictionaries NIPS 2011
How biased are maximum entropy models? NIPS 2011
A General Linear Non-Gaussian State-Space Model: Identifiability, Identification, and Applications ACML 2011
Quadratic Weighted Automata:Spectral Algorithm and Likelihood Maximization ACML 2011
Computationally Efficient Sufficient Dimension Reduction via Squared-Loss Mutual Information ACML 2011
Learning Attribute-weighted Voter Model over Social Networks ACML 2011
The Neural Autoregressive Distribution Estimator AISTATS 2011
Spectral Dimensionality Reduction via Maximum Entropy AISTATS 2011
Linear-Time Estimators for Propensity Scores AISTATS 2011
On Learning Discrete Graphical Models using Group-Sparse Regularization AISTATS 2011