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Optimization & Theory

6,829 papers (27 classified directly here)

Subtopics

Model Compression (1,785) Optimization (1,664) Efficient Computing (1,579) Theory (1,082) Neural Network Optimization (903) Evaluation (509) Loss Functions (123) Interpretability (105) Stochastic Methods (97) Regularization (77) Generalization (24) Sparse Optimization (7)

Papers per year

8
50
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1173
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Papers (including subtopics)

Guaranteed Sparse Recovery under Linear Transformation ICML 2013
Sharp Generalization Error Bounds for Randomly-projected Classifiers ICML 2013
Fast algorithms for sparse principal component analysis based on Rayleigh quotient iteration ICML 2013
Proximal Newton-type methods for convex optimization NIPS 2012
Learning optimal spike-based representations NIPS 2012
Feature Clustering for Accelerating Parallel Coordinate Descent NIPS 2012
Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison NIPS 2012
Large Scale Distributed Deep Networks NIPS 2012
Scaled Gradients on Grassmann Manifolds for Matrix Completion NIPS 2012
Exact and Stable Recovery of Sequences of Signals with Sparse Increments via Differential _1-Minimization NIPS 2012
Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning NIPS 2012
Stochastic Gradient Descent with Only One Projection NIPS 2012
Sketch-Based Linear Value Function Approximation NIPS 2012
Calibrated Elastic Regularization in Matrix Completion NIPS 2012
Synchronization can Control Regularization in Neural Systems via Correlated Noise Processes NIPS 2012
A Note on Metric Properties for Some Divergence Measures: The Gaussian Case ACML 2012
On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models AISTATS 2012
Deep Learning Made Easier by Linear Transformations in Perceptrons AISTATS 2012
A Differentially Private Stochastic Gradient Descent Algorithm for Multiparty Classification AISTATS 2012
Krylov Subspace Descent for Deep Learning AISTATS 2012
Scaling up Kernel SVM on Limited Resources: A Low-rank Linearization Approach AISTATS 2012
Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent NIPS 2011
Algorithms for Hyper-Parameter Optimization NIPS 2011
Shallow vs. Deep Sum-Product Networks NIPS 2011
Expressive Power and Approximation Errors of Restricted Boltzmann Machines NIPS 2011