Hariharan Narayanan
Hariharan Narayanan
School of Technology and Computer Science, TIFR
Verified email at uw.edu - Homepage
Cited by
Cited by
Sample complexity of testing the manifold hypothesis
H Narayanan, S Mitter
Advances in neural information processing systems, 1786-1794, 2010
Testing the manifold hypothesis
C Fefferman, S Mitter, H Narayanan
Journal of the American Mathematical Society 29 (4), 983-1049, 2016
On the complexity of computing Kostka numbers and Littlewood-Richardson coefficients
H Narayanan
Journal of Algebraic Combinatorics 24 (3), 347-354, 2006
On the relation between low density separation, spectral clustering and graph cuts
H Narayanan, M Belkin, P Niyogi
Advances in Neural Information Processing Systems, 1025-1032, 2007
Random walks on polytopes and an affine interior point method for linear programming
R Kannan, H Narayanan
Mathematics of Operations Research 37 (1), 1-20, 2012
Escaping the local minima via simulated annealing: Optimization of approximately convex functions
A Belloni, T Liang, H Narayanan, A Rakhlin
Conference on Learning Theory, 240-265, 2015
Geometric complexity theory III: on deciding nonvanishing of a Littlewood–Richardson coefficient
KD Mulmuley, H Narayanan, M Sohoni
Journal of Algebraic Combinatorics 36 (1), 103-110, 2012
Random walk approach to regret minimization
H Narayanan, A Rakhlin
Advances in Neural Information Processing Systems, 1777-1785, 2010
Geometric interpretation of half-plane capacity
S Lalley, G Lawler, H Narayanan
Electronic Communications in Probability 14, 566-571, 2009
Reconstruction and Interpolation of Manifolds. I: The Geometric Whitney Problem
C Fefferman, S Ivanov, Y Kurylev, M Lassas, H Narayanan
Foundations of Computational Mathematics, 1-99, 2019
Minimizing average latency in oblivious routing
P Harsha, TP Hayes, H Narayanan, H Räcke, J Radhakrishnan
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete …, 2008
Randomized interior point methods for sampling and optimization
H Narayanan
The Annals of Applied Probability 26 (1), 597-641, 2016
Sampling hypersurfaces through diffusion
H Narayanan, P Niyogi
Approximation, Randomization and Combinatorial Optimization. Algorithms and …, 2008
Heat flow and a faster algorithm to compute the surface area of a convex body
M Belkin, H Narayanan, P Niyogi
2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06 …, 2006
Fitting a putative manifold to noisy data
C Fefferman, S Ivanov, Y Kurylev, M Lassas, H Narayanan
Proceedings of COLT 2018 (Conference On Learning Theory), 2018
On the Sample Complexity of Learning Smooth Cuts on a Manifold.
H Narayanan, P Niyogi
COLT, 2009
Mixing times and ℓp bounds for Oblivious routing
G Lawler, H Narayanan
2009 Proceedings of the Sixth Workshop on Analytic Algorithmics and …, 2009
On zeroth-order stochastic convex optimization via random walks
T Liang, H Narayanan, A Rakhlin
arXiv preprint arXiv:1402.2667, 2014
Estimating certain non-zero Littlewood-Richardson coefficients
H Narayanan
arXiv preprint arXiv:1306.4060, 2013
Efficient sampling from time-varying log-concave distributions
H Narayanan, A Rakhlin
The Journal of Machine Learning Research 18 (1), 4017-4045, 2017
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