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Hariharan Narayanan
Hariharan Narayanan
School of Technology and Computer Science, TIFR
Verified email at tifr.res.in - Homepage
Title
Cited by
Cited by
Year
Testing the manifold hypothesis
C Fefferman, S Mitter, H Narayanan
Journal of the American Mathematical Society 29 (4), 983-1049, 2016
5142016
Sample complexity of testing the manifold hypothesis
H Narayanan, S Mitter
Advances in Neural Information Processing Systems 23, 2010
2532010
On the complexity of computing Kostka numbers and Littlewood-Richardson coefficients
H Narayanan
FPSAC 06, Journal of Algebraic Combinatorics 2006 24 (3), 347-354, 2006
1102006
Random walks on polytopes and an affine interior point method for linear programming
R Kannan, H Narayanan
STOC 09, Mathematics of Operations Research 37 (1), 1-20, 2012
1092012
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
862015
On the relation between low density separation, spectral clustering and graph cuts
H Narayanan, M Belkin, P Niyogi
Advances in Neural Information Processing Systems 19, 2006
722006
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
562012
Reconstruction and interpolation of manifolds. I: The geometric whitney problem
C Fefferman, S Ivanov, Y Kurylev, M Lassas, H Narayanan
Foundations of Computational Mathematics 20 (5), 1035-1133, 2020
47*2020
Fitting a putative manifold to noisy data
C Fefferman, S Ivanov, Y Kurylev, M Lassas, H Narayanan
Conference On Learning Theory, 688-720, 2018
432018
Randomized interior point methods for sampling and optimization
H Narayanan
The Annals of Applied Probability 26 (1), 597-641, 2016
40*2016
Geometric interpretation of half-plane capacity
S Lalley, G Lawler, H Narayanan
Electronic Communications in Probability 14, 566-571, 2009
382009
Random walk approach to regret minimization
H Narayanan, A Rakhlin
Advances in Neural Information Processing Systems 23, 2010
362010
On the Sample Complexity of Learning Smooth Cuts on a Manifold.
H Narayanan, P Niyogi
COLT 09, 2009
252009
Efficient sampling from time-varying log-concave distributions
H Narayanan, A Rakhlin
The Journal of Machine Learning Research 18 (1), 4017-4045, 2017
24*2017
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
222008
On zeroth-order stochastic convex optimization via random walks
T Liang, H Narayanan, A Rakhlin
arXiv preprint arXiv:1402.2667, 2014
182014
Reconstruction of a Riemannian manifold from noisy intrinsic distances
C Fefferman, S Ivanov, M Lassas, H Narayanan
SIAM Journal on Mathematics of Data Science 2 (3), 770-808, 2020
172020
Fitting a manifold of large reach to noisy data
C Fefferman, S Ivanov, M Lassas, H Narayanan
Journal of Topology and Analysis, arXiv preprint arXiv:1910.05084, 2019
172019
Heat flow and a faster algorithm to compute the surface area of a convex body
M Belkin, H Narayanan, P Niyogi
FOCS 06, Random Structures & Algorithms 43 (4), 407-428, 2013
16*2013
Manifold learning using kernel density estimation and local principal components analysis
K Mohammed, H Narayanan
arXiv preprint arXiv:1709.03615, 2017
142017
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Articles 1–20