Boyd, Stephen P.

14 publications

ICLR 2025 An Asynchronous Bundle Method for Distributed Learning Problems Daniel Cederberg, Xuyang Wu, Stephen P. Boyd, Mikael Johansson

TMLR 2024 Disciplined Saddle Programming Philipp Schiele, Eric Sager Luxenberg, Stephen P. Boyd

NeurIPS 2024 Optimization Algorithm Design via Electric Circuits Stephen P. Boyd, Tetiana Parshakova, Ernest K. Ryu, Jaewook J. Suh

FnTML 2021 Minimum-Distortion Embedding Akshay Agrawal, Alnur Ali, Stephen P. Boyd

AAAI 2021 Sample Efficient Reinforcement Learning with REINFORCE Junzi Zhang, Jongho Kim, Brendan O'Donoghue, Stephen P. Boyd

IJCAI 2018 Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data David Hallac, Sagar Vare, Stephen P. Boyd, Jure Leskovec

AISTATS 2017 Learning the Network Structure of Heterogeneous Data via Pairwise Exponential Markov Random Fields Youngsuk Park, David Hallac, Stephen P. Boyd, Jure Leskovec

FnTML 2016 Generalized Low Rank Models Madeleine Udell, Corinne Horn, Reza Zadeh, Stephen P. Boyd

UAI 2015 Disciplined Convex Stochastic Programming: A New Framework for Stochastic Optimization Alnur Ali, J. Zico Kolter, Steven Diamond, Stephen P. Boyd

FnTML 2011 Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers Stephen P. Boyd, Neal Parikh, Eric Chu, Borja Peleato, Jonathan Eckstein

AAAI 2007 A Method for Large-Scale L1-Regularized Logistic Regression Kwangmoo Koh, Seung-Jean Kim, Stephen P. Boyd

ICML 2006 A Duality View of Spectral Methods for Dimensionality Reduction Lin Xiao, Jun Sun, Stephen P. Boyd

ICML 2006 Optimal Kernel Selection in Kernel Fisher Discriminant Analysis Seung-Jean Kim, Alessandro Magnani, Stephen P. Boyd

ICML 2006 Pareto Optimal Linear Classification Seung-Jean Kim, Alessandro Magnani, Sikandar Samar, Stephen P. Boyd, Johan Lim