Brendan O'Donoghue

Ph.D. Thesis

Suboptimal Control Policies via Convex Optimization

B. O'Donoghue


PGQ: Combining policy gradient and Q-learning

Brendan O'Donoghue, Remi Munos, Koray Kavukcuoglu, and Volodymyr Mnih

Large-scale convex optimization for dense wireless cooperative networks

Y. Shi, J. Zhang, B. O’Donoghue, and K. Letaief

Operator splitting for conic optimization via homogeneous self-dual embedding

B. O'Donoghue, E. Chu, N. Parikh, and S. Boyd

A primal-dual operator splitting method for conic optimization

E. Chu, B. O'Donoghue, N. Parikh, and S. Boyd

Approximate dynamic programming via iterated Bellman Inequalities

Y. Wang, B. O'Donoghue, and S. Boyd

Iterated approximate value functions

B. O'Donoghue, Y. Wang, and S. Boyd

A splitting method for optimal control

B. O'Donoghue, G. Stathopoulos, and S. Boyd

Fast alternating direction optimization methods

T. Goldstein, B. O'Donoghue, and S. Setzer

Performance bounds and suboptimal policies for multi-period investment

S. Boyd, M. Mueller, B. O'Donoghue, and Y. Wang

Adaptive restart for accelerated gradient schemes

B. O'Donoghue and E. J. Candès

A spread-return mean-reverting model for credit spread dynamics

B. O'Donoghue, M. Peacock, J. Lee, and L. Capriotti

Min-max approximate dynamic programming

B. O'Donoghue, Y. Wang, and S. Boyd