### 2012

Bouvrie, Jake; Maggioni, Mauro

Efficient Solution of Markov Decision Problems with Multiscale Representations Inproceedings

In: Proc. 50th Annual Allerton Conference on Communication, Control, and Computing, 2012.

BibTeX | Tags: Machine learning, reinforcement learning, representation learning

@inproceedings{BM_EfficientMultiscaleMarkov,

title = {Efficient Solution of Markov Decision Problems with Multiscale Representations},

author = {Jake Bouvrie and Mauro Maggioni},

year = {2012},

date = {2012-01-01},

booktitle = {Proc. 50th Annual Allerton Conference on Communication, Control, and Computing},

keywords = {Machine learning, reinforcement learning, representation learning},

pubstate = {published},

tppubtype = {inproceedings}

}

Bouvrie, Jake; Maggioni, Mauro

Multiscale Markov Decision Problems: Compression, Solution, and Transfer Learning Journal Article

In: 2012.

Links | BibTeX | Tags: Machine learning, multiscale analysis, reinforcement learning, representation learning, spectral graph theory, transfer learning

@article{BM:MMDPs,

title = {Multiscale Markov Decision Problems: Compression, Solution, and Transfer Learning},

author = {Jake Bouvrie and Mauro Maggioni},

url = {http://arxiv.org/abs/1212.1143},

year = {2012},

date = {2012-01-01},

keywords = {Machine learning, multiscale analysis, reinforcement learning, representation learning, spectral graph theory, transfer learning},

pubstate = {published},

tppubtype = {article}

}

### 2007

Mahadevan, Sridhar; Maggioni, Mauro

Proto-value Functions: A Spectral Framework for Solving Markov Decision Processes Journal Article

In: JMLR, vol. 8, pp. 2169–2231, 2007.

BibTeX | Tags: diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory

@article{smmm:jmrl1,

title = {Proto-value Functions: A Spectral Framework for Solving Markov Decision Processes},

author = {Sridhar Mahadevan and Mauro Maggioni},

year = {2007},

date = {2007-01-01},

journal = {JMLR},

volume = {8},

pages = {2169--2231},

keywords = {diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory},

pubstate = {published},

tppubtype = {article}

}

### 2006

Maggioni, Mauro; Mahadevan, Sridhar

Fast Direct Policy Evaluation using Multiscale Analysis of Markov Diffusion Processes Inproceedings

In: ICML 2006, pp. 601–608, 2006.

BibTeX | Tags: diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory

@inproceedings{smmm:FastDirectMDP,

title = {Fast Direct Policy Evaluation using Multiscale Analysis of Markov Diffusion Processes},

author = {Mauro Maggioni and Sridhar Mahadevan},

year = {2006},

date = {2006-01-01},

booktitle = {ICML 2006},

pages = {601--608},

keywords = {diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory},

pubstate = {published},

tppubtype = {inproceedings}

}

Mahadevan, Sridhar; Ferguson, Kim; Osentoski, Sarah; Maggioni, Mauro

Simultaneous Learning of Representation and Control In Continuous Domains Inproceedings

In: AAAI, AAAI Press, 2006.

BibTeX | Tags: diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory

@inproceedings{smkfsomm:SimLearningReprControlContinuous,

title = {Simultaneous Learning of Representation and Control In Continuous Domains},

author = {Sridhar Mahadevan and Kim Ferguson and Sarah Osentoski and Mauro Maggioni},

year = {2006},

date = {2006-01-01},

booktitle = {AAAI},

publisher = {AAAI Press},

keywords = {diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory},

pubstate = {published},

tppubtype = {inproceedings}

}

### 2005

Mahadevan, Sridhar; Maggioni, Mauro

Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions Inproceedings

In: University of Massachusetts, Department of Computer Science Technical Report TR-2005-38; Proc. NIPS 2005, 2005.

BibTeX | Tags: diffusion geometry, diffusion wavelets, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory

@inproceedings{smmm:ValueFunction,

title = {Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions},

author = {Sridhar Mahadevan and Mauro Maggioni},

year = {2005},

date = {2005-01-01},

booktitle = {University of Massachusetts, Department of Computer Science Technical Report TR-2005-38; Proc. NIPS 2005},

keywords = {diffusion geometry, diffusion wavelets, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory},

pubstate = {published},

tppubtype = {inproceedings}

}

- Lectures at Summer School at Peking University, July 2017.
- PCMI Lectures, Summer 2016: Lecture 1, Lecture 2, Problems/discussion points
- Google Scholar
- Papers on the ArXiv
- Papers on MathsciNet
- Tutorials on diffusion geometry and multiscale analysis on graphs at the MRA Internet Program at IPAM: Part I and Part II.
- Diffusion Geometries, Diffusion Wavelets and Harmonic Analysis of large data sets, IPAM, Multiscale Geometric Analysis Program, Fall 2004.
- Diffusion Geometries, global and multiscale, IPAM, 2005.