University of Southern California
Machine Learning Center

Publications

 

Conference Publications

D. Deng, C. Shahabi, U. Demiryurek, L. Zhu, R. Yu and Y. Liu. Latent Space Model for Road Networks to Predict Time-Varying Traffic. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016), 2016

R. Ge, J. D. Lee, and T. Ma. Matrix Completion has No Spurious Local Minima. In Advances in Neural Information Processing Systems (NIPS 2016), 2016

D. Cheng, R. Peng, I. Perros, and Y. Liu. SPALS: Fast Alternating Least Squares via Implicit Leverage Scores Sampling. In Advances in Neural Information Processing Systems (NIPS 2016), 2016

S. Gao, G. Ver Steeg, and A. Galstyan. Variational Information Maximization for Feature Selection. In Advances in Neural Information Processing Systems (NIPS 2016), 2016

X. He, K. Xu, D. Kempe and Y. Liu. Learning Influence Functions from Incomplete Observations. In Advances in Neural Information Processing Systems (NIPS), 2016

J. D. Lee, M. Simchowitz, M. I. Jordan, and B. Recht. Gradient Descent Converges to Minimizers. In Conference on Learning Theory (COLT 2016), 2016

I. Diakonikolas, D. Kane, A. Stewart . Optimal Learning via the Fourier Transform for Sums of Independent Integer Random Variables. In Conference on Learning Theory (COLT 2016), 2016

I. Diakonikolas, G. Kamath, D. Kane, J. Li, A. Moitra, A. Stewart . Robust Estimators in High Dimensions without the Computational Intractability. In IEEE Symposium on Foundations of Computer Science (FOCS 2016) , 2016

I Diakonikolas, D. Kane. A New Approach for Testing Properties of Discrete Distributions. In IEEE Symposium on Foundations of Computer Science (FOCS 2016) , 2016

S. Tu, R. Boczar, M. Soltanolkotabi, and B. Recht. Low-rank Solutions of Linear Matrix Equations via Procrustes Flow.. In International Conference on Machine Learning (ICML 2016), 2016

J. Acharya, I. Diakonikolas, J. Li, L. Schmidt . Fast Algorithms for Segmented Regression. In International Conference on Machine Learning (ICML 2016), 2016

R. Yu and Y. Liu. Learning from Multiway Data: Simple and Efficient Tensor Regression. In International Conference on Machine Learning (ICML 2016), 2016

Yoon Sik Cho, Emilio Ferrara, Greg Ver Steeg, and Aram Galstyan. Latent Space Models for Multimodal Social Data. In World Wide Web Conference (WWW 2016), 2016

Z. Che, D. Kale, W. Li, M. T. Bahadori, and Y. Liu. Deep Computational Phenotyping. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015), 2015

I. Diakonikolas, M. Hardt, L. Schmidt. Differentially Private Learning of Structured Discrete Distributions. In Advances in Neural Information Processing Systems (NIPS 2015), 2015

M. Razaviyayn, F. Farnia, and D. Tse. Discrete Rènyi classifiers. In Advances in Neural Information Processing Systems (NIPS 2016), 2015

S. Gao, G. Ver Steeg, and A. Galstyan. Efficient Estimation of Mutual Information for Strongly Dependent Variables . In Artificial Intelligence and Statistics Conference (AISTATS 2015), 2015

D. Cheng, Y. Cheng, Y. Liu, R. Peng, and S.-H. Teng. Efficient Sampling for Gaussian Graphical Models via Spectral Sparsification. In Conference on Learning Theory (COLT 15), 2015

R. Yu, D. Cheng and Y. Liu. Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams. In International Conference on Machine Learning (ICML 2015), 2015

M. T. Bahadori, D. Kale, Y. Fan, and Y. Liu. Functional Subspace Clustering with Application to Time Series. In International Conference on Machine Learning (ICML 2015), 2015

S. Chan, I. Diakonikolas, R. Servedio, X. Sun . Near-Optimal Density Estimation in Near-Linear Time Using Variable-Width Histograms. In Advances in Neural Information Processing Systems (NIPS 2014), 2014

G. Ver Steeg and A. Galstyan. Discovering Structure in High-Dimensional Data Through Correlation Explanation. In Advances in Neural Information Processing Systems (NIPS 2014), 2014

S. Chan, I. Diakonikolas, R. Servedio, X. Sun . Efficient Density Estimation via Piecewise Polynomial Approximation. In Annual ACM Symposium on Theory of Computing (STOC 2014), 2014

X. He, T. Rekatsinas, J. Foulds, L. Getoor, Y. Liu. HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades. In International Conference on Machine Learning (ICML 2015),

 

Journal Publications

Jason D. Lee, Dennis L Sun, Yuekai Sun, and Jonathan Taylor.. Exact Post-Selection Inference with the Lasso. In Annals of Statistics, 2016

M. Hong, M. Razaviyayn, Z.-Q. Luo, J.-S. Pang. A unified algorithmic framework for block-structured optimization involving big data: With applications in machine learning and signal processing. In IEEE Signal Processing Magazine, 2016

N. Nayyar, D. Kalathil and R. Jain. On regret-optimal learning in decentralized multi-armed bandits. In IEEE Trans. on Control of Networked Systems, 2016

Kong, Y., Zheng, Z. and Lv, J.. The constrained Dantzig selector with enhanced consistency. In Journal of Machine Learning Research, 2016

Shang-Hua Teng. Foundations and Trends in Theoretical Computer Science . In Scalable Algorithms for Data and Network Analysis, 2016

S. Oymak, M. Soltanolkotabi, and B. Recht. Sharp Time-data tradeoffs for linear inverse problems. In Submitted to IEEE Trans. on Information Theory, 2016

Minsker, S.. Sub-Gaussian estimators of the mean of a random matrix with heavy-tailed entries.. In Submitted to the Annals of Statistics, 2016

Fan, Y. and Lv, J.. Innovated scalable efficient estimation in ultra-large Gaussian graphical models. In The Annals of Statistics, 2016

Minsker, S.. Geometric median and robust estimation in Banach spaces. In Bernoulli, 2015

D. Kalathil, V. Borkar and R. Jain,. Empirical Q-Value Iteration. In Submitted to Stochastic Systems, 2015