开课单位--德克萨斯大学
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1
Information Theoretic Regularization for Semi-Supervised Boosting [半监督提升的信息论正则化]
  Lei Zheng(德克萨斯大学) We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradi...
热度:62

2
Groups-Keeping Solution Path Algorithm for Sparse Regression with Automatic Feature Grouping[自动特征分组稀疏回归的保组解路径算法]
  黄恒(德克萨斯大学) Feature selection is one of the most important data mining research topics with many applications. In practical problems, features often have group st...
热度:5

3
Bayesian entropy estimation for binary spike train data using parametric prior knowledge[基于参数先验知识的二值尖峰序列数据贝叶斯熵估计]
  Evan W.Archer(德克萨斯大学) Shannon's entropy is a basic quantity in information theory, and a fundamental building block for the analysis of neural codes. Estimating the ent...
热度:11

4
Computational and mathematical challenges involved in estimating[推理中涉及的计算和数学挑战]
  Tandy Warnow(德克萨斯大学) Phylogenetic inference presents enormous computational and mathematical challenges, but these are particularly exacerbated when dealing with very larg...
热度:71

5
Provable Matrix Completion using Alternating Minimization[交替极小化的可证矩阵完备化 ]
  Praneeth Netrapalli(德克萨斯大学) Alternating minimization has emerged as a popular heuristic for large-scale machine learning problems involving low-rank matrices. However, there have...
热度:67

6
The Qualitative Learner of Action and Perception, QLAP[行为和感知的定性学习,QLAP]
  Benjamin Kuipers;Jonathan Mugan(德克萨斯大学) This video presents an introduction to the Qualitative Learner of Action and Perception, QLAP. QLAP autonomously learns a useful state abstraction and...
热度:34

7
A Framework for Simultaneous Co-clustering and Learning from Complex Data [一种同时聚类和复杂数据的学习框架]
  Meghana Deodhar(德克萨斯大学) For difficult classification or regression problems, practitioners often segment the data into relatively homogenous groups and then build a model for...
热度:77

8
Practical RL: Representation, interaction, synthesis, and morality (PRISM)[实践RL:表现、互动、综合和道德(棱镜)]
  Peter Stone(德克萨斯大学) When scaling up Reinforcement Learning (RL) to large continuous domains with imperfect representations and hierarchical structure, we often try applyi...
热度:24

9
Words as reflections of psychological state[语言作为心理状态的反映]
  James W. Pennebaker(德克萨斯大学) Pennebaker’s research explores the links between traumatic experiences, expressive writing, natural language use, and physical and mental health...
热度:22

10
Object-Graphs for Context-Aware Category Discovery[上下文感知类别发现的对象图]
   Yong Jae Lee(德克萨斯大学) How can knowing about some categories help us to dis- cover new ones in unlabeled images? Unsupervised visual category discovery is useful to mine for...
热度:34
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