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Optimization & Theory

36,874 papers (3 classified directly here)

Subtopics

Optimization (14,983) Bayesian Inference (5,566) Learning Theory (5,334) Theory (4,955) Statistical Learning (4,117) Neural Network Optimization (3,649) Stochastic Processes (2,667) Loss Functions (1,162) Distributed Learning (1,135) Stochastic Methods (1,118) Online Algorithms (806) Statistics (684) Information Theory (318) Generalization (220) Sparse Optimization (158) Sample Complexity (99) Game Theory (30) Robust Optimization (17) Optimal Transport (14) Approximation Algorithms (10) Distributed Optimization (8) Convex Optimization (8)

Papers per year

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Papers (including subtopics)

Particle Filtering for Nonparametric Bayesian Matrix Factorization NIPS 2006
Large-Scale Sparsified Manifold Regularization NIPS 2006
Non-rigid point set registration: Coherent Point Drift NIPS 2006
Active learning for misspecified generalized linear models NIPS 2006
Tighter PAC-Bayes Bounds NIPS 2006
A Bayesian Approach to Diffusion Models of Decision-Making and Response Time NIPS 2006
A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation NIPS 2006
Dirichlet-Enhanced Spam Filtering based on Biased Samples NIPS 2006
Stability of $K$-Means Clustering NIPS 2006
Convergence of Laplacian Eigenmaps NIPS 2006
Bayesian Policy Gradient Algorithms NIPS 2006
Greedy Layer-Wise Training of Deep Networks NIPS 2006
Optimal Change-Detection and Spiking Neurons NIPS 2006
Temporal dynamics of information content carried by neurons in the primary visual cortex NIPS 2006
Automated Hierarchy Discovery for Planning in Partially Observable Environments NIPS 2006
On Transductive Regression NIPS 2006
Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural Prosthesis NIPS 2006
Learning annotated hierarchies from relational data NIPS 2006
iLSTD: Eligibility Traces and Convergence Analysis NIPS 2006
Nonnegative Sparse PCA NIPS 2006
PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier NIPS 2006
Generalized Regularized Least-Squares Learning with Predefined Features in a Hilbert Space NIPS 2006
Map-Reduce for Machine Learning on Multicore NIPS 2006
Real-time adaptive information-theoretic optimization of neurophysiology experiments NIPS 2006
High-Dimensional Graphical Model Selection Using $\ell_1$-Regularized Logistic Regression NIPS 2006