Papers

Learning Theory

Sample Complexity of Testing the Manifold Hypothesis.
Hariharan Narayanan and Sanjoy Mitter
Neural Information Processing Systems (NIPS), December 2010.
[pdf]

Random walk approach to Regret Minimization.
Hariharan Narayanan and Alexander Rakhlin
Neural Information Processing Systems (NIPS), December 2010.
[pdf]

On the Sample Complexity of Learning Smooth Cuts on a Manifold.
Hariharan Narayanan and Partha Niyogi
22nd Annual Conference on Learning Theory (COLT), June 2009
[pdf]

On the relation between Low Density Separation, Spectral Clustering and Graph Cuts.
Hariharan Narayanan, Mikhail Belkin and Partha Niyogi
Neural Information Processing Systems (NIPS), December 2006.
[pdf]
[appendix]

Learning with Spectral Kernels and Heavy Tailed Data.
Michael Mahoney and Hariharan Narayanan
preprint.
[pdf]

Language evolution, Coalescent processes and the Consensus problem on a Social Network
Hariharan Narayanan and Partha Niyogi
preprint
[pdf]

Algorithmic applications of diffusion

Randomized Interior Point Methods for Sampling and Optimization.
Hariharan Narayanan
preprint
[pdf]

Random Walks on Polytopes and an Affine Interior Point Method for Linear Programming.
Ravi Kannan and Hariharan Narayanan
41st ACM Symposium on Theory of Computing (STOC), May 2009
To appear in Mathematics of Operations Research
[pdf]

Sampling Hypersurfaces through Diffusion.
Hariharan Narayanan and Partha Niyogi
12th Intl. Workshop on Randomization and Computation (RANDOM), August 2008
[pdf]

Heat flow and a faster algorithm to compute the surface area of a convex body.
Mikhail Belkin, Hariharan Narayanan and Partha Niyogi
IEEE Conference on Foundations of Computer Science (FOCS), October 2006.
[pdf]

Statistical Physics

Geometric Interpretation of Halfplane Capacity.
Steven Lalley, Gregory Lawler and Hariharan Narayanan
Electronic Communications in Probability, December 2009
[pdf]

Combinatorial Representation Theory

An algorithm for Littlewood-Richardson coefficients, Okounkov's conjecture and Geometric Complexity Theory
Hariharan Narayanan
In preparation
[pdf] of a talk at a [GCT workshop] at the intractability institute.

Geometric Complexity Theory III:Testing nonvanishing of a generalized Littlewood-Richardson coefficient.
Ketan Mulmuley, Hariharan Narayanan and Milind Sohoni
[pdf]
To appear in Journal of Algebraic Combinatorics

On the Complexity of computing Kostka numbers and Littlewood-Richardson coefficients.
Hariharan Narayanan
Formal Power Series and Algebraic Combinatorics (FPSAC), June 2006
Journal of Algebraic Combinatorics, Volume 24 , Issue 3 (November 2006)
[pdf]

Network Algorithms

Mixing Times and lp bounds for Oblivious Routing.
Gregory Lawler and Hariharan Narayanan
Workshop on Analytic Algorithmics and Combinatorics (ANALCO), January 2009
[pdf]

Distributed averaging in the presence of a sparse cut.
Hariharan Narayanan
ACM Symposium on Principles of Distributed Computing (PODC), August 2008
[pdf]

Minimizing Average Latency in Oblivious Routing.
Prahladh Harsha, Tom Hayes, Hariharan Narayanan, Harald Räcke and Jaikumar Radhakrishnan
ACM-SIAM Symposium on Discrete Algorithms (SODA), January 2008
[pdf]

Geographic Gossip on Geometric Random Graphs via Affine Combinations.
Hariharan Narayanan
ACM Symposium on Principles of Distributed Computing (PODC), August 2007
[pdf]

Undergraduate Work

Service manual for a Bluetooth Enabled Neonatal Monitor.
A. Jain, S. Mahajan, H. Narayanan and P. Shah
[pdf]
Report in the IITB alumni magazine on this project : [pdf]

Random Trees in Electrical networks.
[pdf]

Damped random walks and the characteristic polynomial of the weighted graph Laplacian.
M. P. Desai and H. Narayanan
[pdf]

Theses

Diffusion in Computer Science and Statistics.
August 2009
Advisor: Partha Niyogi
[pdf]

Green's functions and the Laplacian on planar graphs.
Thesis for a Master's Degree in Electrical Engineering from IIT Bombay.
[ps]

Volumes of Codimension 1 Manifolds and a Randomized Polynomial-Time Algorithm
to Compute the Surface Area of a Smooth Convex Body.
Thesis for a Master's Degree in Computer Science from the University of Chicago









Copyright Notice

The documents distributed by this server have been provided by the contributing authors as a means to ensure timely dissemination of scholarly and technical work on a noncommercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.



[Main Page]