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NN
2010
Springer
187views Neural Networks» more  NN 2010»
14 years 8 months ago
Efficient exploration through active learning for value function approximation in reinforcement learning
Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...
Takayuki Akiyama, Hirotaka Hachiya, Masashi Sugiya...
146
Voted
HCI
2011
14 years 5 months ago
Visually Exploring Multivariate Trends in Patient Cohorts Using Animated Scatter Plots
Abstract. The effectiveness of animation in visualization is an interesting research topic that led to contradicting results in the past. On top of that, we are facing three addit...
Alexander Rind, Wolfgang Aigner, Silvia Miksch, Sy...
ICDE
2009
IEEE
205views Database» more  ICDE 2009»
16 years 3 months ago
Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-Shaped (RDF) Data
Keyword queries enjoy widespread usage as they represent an intuitive way of specifying information needs. Recently, answering keyword queries on graph-structured data has emerged ...
Thanh Tran, Haofen Wang, Sebastian Rudolph, Philip...
236
Voted
ICDE
2009
IEEE
131views Database» more  ICDE 2009»
16 years 3 months ago
Exploring a Few Good Tuples from Text Databases
Information extraction from text databases is a useful paradigm to populate relational tables and unlock the considerable value hidden in plain-text documents. However, information...
Alpa Jain, Divesh Srivastava
ICML
2002
IEEE
16 years 2 months ago
Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
Carlos Guestrin, Relu Patrascu, Dale Schuurmans