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Št. zadetkov: 6
Generalization theory of two-part code MDL estimator
Tong Zhang
Video in druga učna gradiva
Oznake: computer science;machine learning;statistical learning
I will present a finite-sample generalization analysis of two-part code MDL estimator. This method selects a model that minimizes the sum of the model description length plus the data description length given the model. It can be shown that under various conditions, optimal rate of convergence can b ...
Leto: 2008 Vir: videolectures.net
Predictive methods for Text mining
Tong Zhang
Video in druga učna gradiva
Oznake: computer science;text mining
I will give a general overview of using prediction methods in text mining applications, including text categorization, information extraction, summarization, and question answering. I will then discuss some of the more advanced issues encountered in real applications such as structured and complicat ...
Leto: 2006 Vir: videolectures.net
Large Scale Ranking Problem: some theoretical and algorithmic issues
Tong Zhang
Video in druga učna gradiva
Oznake: computer science;information retrieval;web mining
The talk is divided into two parts. The first part focuses on web-search ranking, for which I discuss training relevance models based on DCG (discounted cumulated gain) optimization. Under this metric, the system output quality is naturally determined by the performance near the top of its rank-list ...
Leto: 2006 Vir: videolectures.net
Convergence of MDL and Bayesian Methods
Tong Zhang
Video in druga učna gradiva
Oznake: computer science;machine learning;bayesian learning
We introduce a complexity measure which we call KL-complexity. Based on this concept, we present a general information exponential inequality that measures the statistical complexity of some deterministic and randomized estimators. We show that simple and clean finite sample convergence bounds can b ...
Leto: 2004 Vir: videolectures.net
Learning with structured inputs
Tong Zhang
Video in druga učna gradiva
Oznake:
I will present a novel approach to semi-supervised learning that employs a method which we refer to as structural learning (aka multi-task learning). The idea is to learn predictive structures from many auxiliary problems that are created from the unlabeled data (and are related to the target pro ...
Leto: 2006 Vir: videolectures.net
Algorithmic Strategies for Non-convex Optimization in Sparse Learning
Tong Zhang
Video in druga učna gradiva
Oznake: computer science;machine learning;statistical learning
We consider optimization formulations with non-convex regularization that are natural for learning sparse linear models. There are two approaches to this problem: 1. Heuristic methods such as gradient descent that only find a local minimum; a drawback of this approach is the lack of theoretical guar ...
Leto: 2009 Vir: videolectures.net
Št. zadetkov: 6
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