Rong Ge
Assistant Professor of Computer Science
Current Appointments & Affiliations
 Assistant Professor of Computer Science, Computer Science, Trinity College of Arts & Sciences 2015
Contact Information
 Background

Education, Training, & Certifications
 Ph.D., Princeton University 2013
 Research

Selected Grants
 Publications & Artistic Works

Selected Publications

Conference Papers
 Arora, S, Ge, R, Ma, T, and Risteski, A. "Provable learning of noisyor networks." June 19, 2017. Full Text
 Azar, Y, Ganesh, A, Ge, R, and Panigrahi, D. "Online service with delay." June 19, 2017. Full Text
 Arora, S, Ge, R, Liang, Y, Ma, T, and Zhang, Y. "Generalization and equilibrium in generative adversarial nets (GANs)." January 1, 2017.
 Ge, R, Jin, C, and Zheng, Y. "No spurious local minima in nonconvex low rank problems: A unified geometric analysis." January 1, 2017.
 Ge, R, and Ma, T. "On the optimization landscape of tensor decompositions." January 1, 2017.
 Jin, C, Ge, R, Netrapalli, P, Kakade, SM, and Jordan, MI. "How to escape saddle points efficiently." January 1, 2017.
 Arora, S, Ge, R, Kannan, R, and Moitra, A. "Computing a Nonnegative Matrix FactorizationProvably." January 2016. Full Text
 Arora, S, Ge, R, Koehler, F, Ma, T, and Moitra, A. "Provable algorithms for inference in topic models." January 1, 2016.
 Ge, R, Jin, C, Kakade, S, Netrapalli, P, and Sidford, A. "Efficient algorithms for largescale generalized eigenvector computation and canonical correlation analysis." January 1, 2016.
 Ge, R, Lee, JD, and Ma, T. "Matrix completion has no spurious local minimum." January 1, 2016.
 Ge, R, and Zou, J. "Rich component analysis." January 1, 2016.
 Ge, R, and Ma, T. "Decomposing overcomplete 3rd order tensors using sumofsquares algorithms." August 1, 2015. Full Text
 Ge, R, Huang, Q, and Kakade, SM. "Learning mixtures of gaussians in high dimensions." June 14, 2015. Full Text
 Anandkumar, A, Ge, R, Hsu, D, Kakade, SM, and Telgarsky, M. "Tensor decompositions for learning latent variable models (A survey for ALT)." January 1, 2015. Full Text
 Anandkumar, A, Ge, R, and Janzamin, M. "Learning overcomplete latent variable models through tensor methods." January 1, 2015.
 Arora, S, Ge, R, Ma, T, and Moitra, A. "Simple, efficient, and neural algorithms for sparse coding." January 1, 2015.
 Frostig, R, Ge, R, Kakade, SM, and Sidford, A. "Competing with the empirical risk minimizer in a single pass." January 1, 2015.
 Frostig, R, Ge, R, Kakade, SM, and Sidford, A. "Unregularizing: Approximate proximal point and faster stochastic algorithms for empirical risk minimization." January 1, 2015.
 Ge, R, Huang, F, Jin, C, and Yuan, Y. "Escaping from saddle points: Online stochastic gradient for tensor decomposition." January 1, 2015.
 Ge, R, and Zou, J. "Intersecting faces: Nonnegative matrix factorization with new guarantees." January 1, 2015.

Journal Articles
 Arora, S, Ge, R, Halpern, Y, Mimno, D, Moitra, A, Sontag, D, Wu, Y, and Zhu, M. "Learning topic models  provably and efficiently." Communications of the Acm 61, no. 4 (March 26, 2018): 8593. Full Text
 Anandkumar, A, Ge, R, and Janzamin, M. "Analyzing tensor power method dynamics in overcomplete regime." Journal of Machine Learning Research 18 (April 1, 2017): 140.
 Huang, Q, Ge, R, Kakade, S, and Dahleh, M. "Minimal Realization Problems for Hidden Markov Models." IEEE Transactions on Signal Processing 64, no. 7 (April 2016): 18961904. Full Text
 Arora, S, Ge, R, Moitra, A, and Sachdeva, S. "Provable ICA with Unknown Gaussian Noise, and Implications for Gaussian Mixtures and Autoencoders." Algorithmica 72, no. 1 (May 2015): 215236. Full Text
 Anandkumar, A, Ge, R, Hsu, D, Kakade, SM, and Telgarsky, M. "Tensor decompositions for learning latent variable models." Journal of Machine Learning Research 15 (August 1, 2014): 27732832.
 Huang, Q, Ge, R, Kakade, S, and Dahleh, M. "Minimal realization problem for Hidden Markov Models." 2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014 (January 30, 2014): 411. Full Text
 Anandkumar, A, Ge, R, Hsu, D, and Kakade, SM. "A tensor approach to learning mixed membership community models." Journal of Machine Learning Research 15 (January 1, 2014): 22392312.
 Arora, S, Bhaskara, A, Ge, R, and Ma, T. "Provable bounds for learning some deep representations." 31st International Conference on Machine Learning, ICML 2014 1 (January 1, 2014): 883891.
 Arora, S, Ge, R, and Moitra, A. "New algorithms for learning incoherent and overcomplete dictionaries." Journal of Machine Learning Research 35 (January 1, 2014): 779806.
 Arora, S, Ge, R, and Sinop, AK. "Towards a better approximation for SPARSEST CUT?." Proceedings  Annual IEEE Symposium on Foundations of Computer Science, FOCS (December 1, 2013): 270279. Full Text
 Anandkumar, A, Ge, R, Hsu, D, and Kakade, SM. "A tensor spectral approach to learning mixed membership community models." Journal of Machine Learning Research 30 (January 1, 2013): 867881.
 Arora, S, Ge, R, Halpern, Y, Mimno, D, Moitra, A, Sontag, D, Wu, Y, and Zhu, M. "A practical algorithm for topic modeling with provable guarantees." 30th International Conference on Machine Learning, ICML 2013 , no. PART 2 (January 1, 2013): 939947.
 Arora, S, Ge, R, Moitra, A, and Sachdeva, S. "Provable ICA with unknown Gaussian noise, with implications for Gaussian mixtures and autoencoders." Advances in Neural Information Processing Systems 3 (December 1, 2012): 23752383.
 Arora, S, Ge, R, and Moitra, A. "Learning topic models  Going beyond SVD." Proceedings Annual Ieee Symposium on Foundations of Computer Science, Focs (December 1, 2012): 110. Full Text
 Arora, S, Ge, R, Sachdeva, S, and Schoenebeck, G. "Finding overlapping communities in social networks: Toward a rigorous approach." Proceedings of the ACM Conference on Electronic Commerce (July 10, 2012): 3754. Full Text
 Arora, S, Ge, R, Kannan, R, and Moitra, A. "Computing a nonnegative matrix factorization  Provably." Proceedings of the Annual ACM Symposium on Theory of Computing (June 26, 2012): 145161. Full Text
 Dai, D, and Ge, R. "Another Subexponential Algorithm for the Simple Stochastic Game." Algorithmica 61, no. 4 (December 2011): 10921104. Full Text
 Arora, S, and Ge, R. "New tools for graph coloring." Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6845 LNCS (September 8, 2011): 112. Full Text
 Arora, S, and Ge, R. "New algorithms for learning in presence of errors." Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6755 LNCS, no. PART 1 (July 11, 2011): 403415. Full Text
 Arora, S, Barak, B, Brunnermeier, M, and Ge, R. "Computational complexity and information asymmetry in financial products." Communications of the ACM 54, no. 5 (May 1, 2011): 101101. Full Text
 Dai, D, and Ge, R. "New results on simple stochastic games." Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5878 LNCS (December 1, 2009): 10141023. Full Text

 Teaching & Mentoring

Recent Courses
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