2008 |
32 | EE | Hariharan Narayanan,
Partha Niyogi:
Sampling Hypersurfaces through Diffusion.
APPROX-RANDOM 2008: 535-548 |
31 | EE | Partha Niyogi,
Stephen Smale,
Shmuel Weinberger:
Finding the Homology of Submanifolds with High Confidence from Random Samples.
Discrete & Computational Geometry 39(1-3): 419-441 (2008) |
30 | EE | Mikhail Belkin,
Partha Niyogi:
Towards a theoretical foundation for Laplacian-based manifold methods.
J. Comput. Syst. Sci. 74(8): 1289-1308 (2008) |
2006 |
29 | EE | Ha Quang Minh,
Partha Niyogi,
Yuan Yao:
Mercer's Theorem, Feature Maps, and Smoothing.
COLT 2006: 154-168 |
28 | EE | Mikhail Belkin,
Hariharan Narayanan,
Partha Niyogi:
Heat Flow and a Faster Algorithm to Compute the Surface Area of a Convex Body.
FOCS 2006: 47-56 |
27 | EE | Hariharan Narayanan,
Mikhail Belkin,
Partha Niyogi:
On the Relation Between Low Density Separation, Spectral Clustering and Graph Cuts.
NIPS 2006: 1025-1032 |
26 | EE | Mikhail Belkin,
Partha Niyogi:
Convergence of Laplacian Eigenmaps.
NIPS 2006: 129-136 |
25 | EE | Sayan Mukherjee,
Partha Niyogi,
Tomaso Poggio,
Ryan M. Rifkin:
Learning theory: stability is sufficient for generalization and necessary and sufficient for consistency of empirical risk minimization.
Adv. Comput. Math. 25(1-3): 161-193 (2006) |
24 | EE | Mikhail Belkin,
Partha Niyogi,
Vikas Sindhwani:
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples.
Journal of Machine Learning Research 7: 2399-2434 (2006) |
2005 |
23 | EE | Shivani Agarwal,
Partha Niyogi:
Stability and Generalization of Bipartite Ranking Algorithms.
COLT 2005: 32-47 |
22 | EE | Mikhail Belkin,
Partha Niyogi:
Towards a Theoretical Foundation for Laplacian-Based Manifold Methods.
COLT 2005: 486-500 |
21 | EE | Vikas Sindhwani,
Partha Niyogi,
Mikhail Belkin:
Beyond the point cloud: from transductive to semi-supervised learning.
ICML 2005: 824-831 |
20 | EE | Xiaofei He,
Deng Cai,
Partha Niyogi:
Laplacian Score for Feature Selection.
NIPS 2005 |
19 | EE | Xiaofei He,
Deng Cai,
Partha Niyogi:
Tensor Subspace Analysis.
NIPS 2005 |
18 | EE | Xiaofei He,
Shuicheng Yan,
Yuxiao Hu,
Partha Niyogi,
HongJiang Zhang:
Face Recognition Using Laplacianfaces.
IEEE Trans. Pattern Anal. Mach. Intell. 27(3): 328-340 (2005) |
2004 |
17 | EE | Mikhail Belkin,
Irina Matveeva,
Partha Niyogi:
Regularization and Semi-supervised Learning on Large Graphs.
COLT 2004: 624-638 |
16 | EE | Natalia Komarova,
Partha Niyogi:
Optimizing the mutual intelligibility of linguistic agents in a shared world.
Artif. Intell. 154(1-2): 1-42 (2004) |
15 | EE | Mikhail Belkin,
Partha Niyogi:
Semi-Supervised Learning on Riemannian Manifolds.
Machine Learning 56(1-3): 209-239 (2004) |
2003 |
14 | EE | Xiaofei He,
Partha Niyogi:
Locality Preserving Projections.
NIPS 2003 |
13 | EE | Dinoj Surendran,
Partha Niyogi:
Measuring the Functional Load of Phonological Contrasts
CoRR cs.CL/0311036: (2003) |
12 | EE | Mikhail Belkin,
Partha Niyogi:
Laplacian Eigenmaps for Dimensionality Reduction and Data Representation.
Neural Computation 15(6): 1373-1396 (2003) |
11 | EE | Partha Niyogi,
Padma Ramesh:
The voicing feature for stop consonants: recognition experiments with continuously spoken alphabets.
Speech Communication 41(2-3): 349-367 (2003) |
2002 |
10 | EE | Mikhail Belkin,
Partha Niyogi:
Using Manifold Stucture for Partially Labeled Classification.
NIPS 2002: 929-936 |
9 | | Samuel Kutin,
Partha Niyogi:
Almost-everywhere Algorithmic Stability and Generalization Error.
UAI 2002: 275-282 |
2001 |
8 | EE | Mikhail Belkin,
Partha Niyogi:
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering.
NIPS 2001: 585-591 |
2000 |
7 | | Partha Niyogi,
Narendra Karmarkar:
An Approach to Data Reduction and Clustering with Theoretical Guarantees.
ICML 2000: 679-686 |
1999 |
6 | EE | Partha Niyogi,
Federico Girosi:
Generalization bounds for function approximation from scattered noisy data.
Adv. Comput. Math. 10(1): 51-80 (1999) |
1998 |
5 | EE | Partha Niyogi,
Kah Kay Sung:
Epsilon focusing--A strategy for active example selection.
Knowl.-Based Syst. 10(7): 441-447 (1998) |
1995 |
4 | | Partha Niyogi:
Free to Choose: Investigating the Sample Complexity of Active Learning of Real Valued Functions.
ICML 1995: 405-412 |
3 | EE | Partha Niyogi,
Robert C. Berwick:
A Note on Zipf's Law, Natural Languages, and Noncoding DNA regions.
CoRR cmp-lg/9503012: (1995) |
1994 |
2 | | Partha Niyogi,
Robert C. Berwick:
A Markov Language Learning Model for Finite Parameter Spaces.
ACL 1994: 171-180 |
1 | EE | Kah Kay Sung,
Partha Niyogi:
Active Learning for Function Approximation.
NIPS 1994: 593-600 |