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12/29/2022
Intrinsic Motivation in Dynamical Control Systems
Biological systems often choose actions without an explicit reward signa...
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03/03/2021
Critical Slowing Down Near Topological Transitions in Rate-Distortion Problems
In Rate Distortion (RD) problems one seeks reduced representations of a ...
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06/08/2020
The Dual Information Bottleneck
The Information Bottleneck (IB) framework is a general characterization ...
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05/11/2019
Semantic categories of artifacts and animals reflect efficient coding
It has been argued that semantic categories across languages reflect pre...
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10/31/2018
An Information-Theoretic Framework for Non-linear Canonical Correlation Analysis
Canonical Correlation Analysis (CCA) is a linear representation learning...
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08/09/2018
Efficient human-like semantic representations via the Information Bottleneck principle
Maintaining efficient semantic representations of the environment is a m...
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05/16/2018
Color naming reflects both perceptual structure and communicative need
Gibson et al. (2017) argued that color naming is shaped by patterns of c...
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12/10/2017
A General Memory-Bounded Learning Algorithm
In an era of big data there is a growing need for memory-bounded learnin...
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11/07/2017
Gaussian Lower Bound for the Information Bottleneck Limit
The Information Bottleneck (IB) is a conceptual method for extracting th...
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09/18/2016
Principled Option Learning in Markov Decision Processes
It is well known that options can make planning more efficient, among th...
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04/18/2016
Memory shapes time perception and intertemporal choices
There is a consensus that human and non-human subjects experience tempor...
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12/21/2015
Information-Theoretic Bounded Rationality
Bounded rationality, that is, decision-making and planning under resourc...
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01/10/2013
Multivariate Information Bottleneck
The Information bottleneck method is an unsupervised non-parametric data...
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10/19/2012
Sufficient Dimensionality Reduction with Irrelevant Statistics
The problem of finding a reduced dimensionality representation of catego...
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07/11/2012
The Minimum Information Principle for Discriminative Learning
Exponential models of distributions are widely used in machine learning ...
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06/27/2012
Bounded Planning in Passive POMDPs
In Passive POMDPs actions do not affect the world state, but still incur...
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04/05/2012
Distribution-Dependent Sample Complexity of Large Margin Learning
We obtain a tight distribution-specific characterization of the sample c...
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07/11/2011
Multi-Instance Learning with Any Hypothesis Class
In the supervised learning setting termed Multiple-Instance Learning (MI...
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11/23/2010