Standout Papers

Laplacian Eigenmaps for Dimensionality Reduction and Data Representation 2003 2026 2010 2018 3.8k
  1. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation (2003)
    Mikhail Belkin, Partha Niyogi Neural Computation
  2. Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples (2006)
    Mikhail Belkin, Partha Niyogi et al. Journal of Machine Learning Research
  3. Reconciling modern machine-learning practice and the classical bias–variance trade-off (2019)
    Mikhail Belkin, Daniel Hsu et al. Proceedings of the National Academy of Sciences

Immediate Impact

4 by Nobel laureates 28 from Science/Nature 102 standout
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1 intermediate paper

Works of Mikhail Belkin being referenced

Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
2003 Standout

Author Peers

Author Last Decade Papers Cites
Mikhail Belkin 3166 301 3654 976 56 7.3k
John Langford 3686 343 3949 819 82 9.1k
Olivier Chapelle 4823 459 3526 540 59 8.9k
Ulrike von Luxburg 2685 330 2047 445 53 6.6k
Yair Weiss 2944 312 4743 577 70 8.9k
Martin J. Wainwright 3980 1169 2348 2251 163 10.5k
Xiaofei He 3613 356 6323 1419 153 10.3k
Keinosuke Fukunaga 3501 421 3985 414 52 9.5k
Vin de Silva 2291 213 3713 708 16 7.8k
Deng Cai 2946 144 4577 676 138 7.0k
Yoram Singer 7185 555 3661 1043 92 11.6k

All Works

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2026