88 citations · 94 across the 13 of their papers we have counts for
14 papers
AltGDA Achieves Global Ergodic Convergence in Matrix Games
Tianlong Nan, Garud Iyengar, Christian Kroer +1
Alternating gradient descent-ascent (AltGDA) is a simple and practically effective method for solving finite two-player zero-sum matrix games. However, the theory of AltGDA remains…
A Domain-Specific Harness for End-to-End Automation of Optimization Research
Heechang Kim, Ernest K. Ryu, Shuvomoy Das Gupta
We present AutoOPT, a domain-specific harness for end-to-end automation of optimization research. AutoOPT organizes the discovery of optimal first-order methods into four stages: n…
On the Convergence of Alternating Gradient Descent-Ascent in Bilinear Games
Tianlong Nan, Shuvomoy Das Gupta, Garud Iyengar +1
We study the alternating gradient descent-ascent (AltGDA) algorithm in two-player zero-sum games. Alternating methods, where players take turns to update their strategies, have lon…
Spatial Branch-and-Bound for Computing Multiplayer Nash Equilibrium
Jakub Černý, Shuvomoy Das Gupta, Christian Kroer
Equilibria of realistic multiplayer games constitute a key solution concept both in practical applications, such as online advertising auctions and electricity markets, and in anal…
The AutoLyap software suite for computer-assisted Lyapunov analyses of first-order methods
Manu Upadhyaya, Shuvomoy Das Gupta, Adrien B. Taylor +2
We introduce AutoLyap, a software suite that assists with Lyapunov analyses of a wide class of first-order methods for structured optimization and inclusion problems. Lyapunov anal…
A Data-Driven Linear Programming Model for Energy-Optimal Metro Timetables
Shuvomoy Das Gupta, Qiuyu Fan, Bart P. G. Van Parys +1
We propose a data-driven linear programming model to compute energy-optimal timetables for networks operating under communications-based train control (CBTC); the model was develop…
Computer-Assisted Design of Accelerated Composite Optimization Methods: OptISTA
Uijeong Jang, Shuvomoy Das Gupta, Ernest K. Ryu
The accelerated composite optimization method FISTA (Beck, Teboulle 2009) is suboptimal by a constant factor, and we present a new method OptISTA that improves FISTA by a constant…
Nonlinear conjugate gradient methods: worst-case convergence rates via computer-assisted analyses
Shuvomoy Das Gupta, Robert M. Freund, Xu Andy Sun +1
We propose a computer-assisted approach to the analysis of the worst-case convergence of nonlinear conjugate gradient methods (NCGMs). Those methods are known for their generally g…
Branch-and-Bound Performance Estimation Programming: A Unified Methodology for Constructing Optimal Optimization Methods
Shuvomoy Das Gupta, Bart P. G. Van Parys, Ernest K. Ryu
We present the Branch-and-Bound Performance Estimation Programming (BnB-PEP), a unified methodology for constructing optimal first-order methods for convex and nonconvex optimizati…
Exterior-point Optimization for Sparse and Low-rank Optimization
Shuvomoy Das Gupta, Bartolomeo Stellato, Bart P. G. Van Parys
Many problems of substantial current interest in machine learning, statistics, and data science can be formulated as sparse and low-rank optimization problems. In this paper, we pr…
On Convergence of Heuristics Based on Douglas-Rachford Splitting and ADMM to Minimize Convex Functions over Nonconvex Sets
Shuvomoy Das Gupta
Recently, heuristics based on the Douglas-Rachford splitting algorithm and the alternating direction method of multipliers (ADMM) have found empirical success in minimizing convex…
On seeking efficient Pareto optimal points in multi-player minimum cost flow problems with application to transportation systems
Shuvomoy Das Gupta, Lacra Pavel
In this paper, we propose a multi-player extension of the minimum cost flow problem inspired by a transportation problem that arises in modern transportation industry. We associate…
A Robust Mixed Integer Optimization Model to Utilize Regenerative Energy of Trains in a Railway Network
Shuvomoy Das Gupta, J. Kevin Tobin, Lacra Pavel
In this paper we present a robust mixed integer optimization model to utilize regenerative braking energy produced by trains in a railway network. An electric train produces regene…
A Two-Step Linear Programming Model for Energy-Efficient Timetables in Metro Railway Networks
Shuvomoy Das Gupta, J. Kevin Tobin, Lacra Pavel
In this paper we propose a novel two-step linear optimization model to calculate energy-efficient timetables in metro railway networks. The resultant timetable minimizes the total…