What Can a Single Neuron Compute?
• Who Does What? A Novel Algorithm to Determine Function
Localization
• Programmable Reinforcement Learning Agents
• From Mixtures of Mixtures to Adaptive Transform Coding
• Dendritic Compartmentalization Could Underlie Competition and
Attentional Biasing of Simultaneous Visual Stimuli
• Place Cells and Spatial Navigation Based on 2D Visual Feature
Extraction, Path Integration, and Reinforcement Learning
• Speech Denoising and Dereverberation Using Probabilistic Models
• Combining ICA and Top-Down Attention for Robust Speech
Recognition
• Modelling Spatial Recall, Mental Imagery and Neglect
• Shape Context: A New Descriptor for Shape Matching and Object
Recognition
• Efficient Learning of Linear Perceptrons
• A Support Vector Method for Clustering
• A Neural Probabilistic Language Model
• A Variational Mean-Field Theory for Sigmoidal Belief Networks 数据挖掘实验室
• Stability and Noise in Biochemical Switches
• Emergence of Movement Sensitive Neurons′ Properties by
Learning a Sparse Code for Natural Moving Images
• New Approaches Towards Robust and Adaptive Speech
Recognition
• Algorithmic Stability and Generalization Performance
• Exact Solutions to Time-Dependent MDPs
• Direct Classification with Indirect Data
• Model Complexity, Goodness of Fit and Diminishing Returns
• A Linear Programming Approach to Novelty Detection
• Decomposition of Reinforcement Learning for Admission Control of
Self-Similar Call Arrival Processes
• Overfitting in Neural Nets: Backpropagation, Conjugate Gradient,
and Early Stopping
• Incremental and Decremental Support Vector Machine Learning
• Vicinal Risk Minimization
http://www.dmresearch.net/uploads/20060102/1000000000.pdf
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