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SUVRIT

Machine learning

"Improving First and Second-Order Methods by Modeling Uncertainty". In Sra, Suvrit; Nowozin, Sebastian; Wright, Stephen J. (eds.). Optimization for Machine

Machine learning

Jensen–Shannon divergence

arXiv:1910.10447. doi:10.1016/j.aim.2021.107595. S2CID 204837864. Sra, Suvrit (2019). "Metrics Induced by Quantum Jensen-Shannon-Renyí and Related Divergences"

Jensen–Shannon divergence

Determinant

http://www.ee.ic.ac.uk/hp/staff/dmb/matrix/proof003.html Lin, Minghua; Sra, Suvrit (2014). "Completely strong superadditivity of generalized matrix functions"

Determinant

Stefanie Jegelka

Professorships in the field of Artificial Intelligence: Stefanie Jegelka and Suvrit Sra were honored with Germany's most highly endowed research award, TU Munich

Stefanie Jegelka

Stochastic gradient descent

Bousquet, Olivier (2012). "The Tradeoffs of Large Scale Learning". In Sra, Suvrit; Nowozin, Sebastian; Wright, Stephen J. (eds.). Optimization for Machine

Stochastic gradient descent

Non-negative matrix factorization

Tensor Tensor decomposition Tensor software Dhillon, Inderjit S.; Sra, Suvrit (2005). "Generalized Nonnegative Matrix Approximations with Bregman Divergences"

Non-negative matrix factorization

Alexander von Humboldt Professorship

environmental humanities scholar Joacim Rocklöv, Swedish epidemiologist Suvrit Sra, mathematician Radu Timofte, Romanian computer scientist Angela Yu,

Alexander von Humboldt Professorship

Hard negative mining

doi:10.1007/978-3-030-58595-2_41. Robinson, Joshua; Chuang, Ching-Yao; Sra, Suvrit; Jegelka, Stefanie (2020). Contrastive Learning with Hard Negative Samples

Hard negative mining