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This thesis investigates the extent to which the optimal value of a constraint satisfaction problem (CSP) can be approximated by some sentence of fixed point logic with counting (FPC). It is known that, assuming $\mathsf{P} \neq…

Logic in Computer Science · Computer Science 2020-08-10 Jamie Tucker-Foltz

In this paper, we focus on a class of constrained nonlinear optimization problems (NLP), where some of its equality constraints define a closed embedded submanifold $\mathcal{M}$ in $\mathbb{R}^n$. Although NLP can be solved directly by…

Optimization and Control · Mathematics 2023-04-05 Nachuan Xiao , Xin Liu , Kim-Chuan Toh

We introduce a class of specially structured linear programming (LP) problems, which has favorable modeling capability for important application problems in different areas such as optimal transport, discrete tomography and economics. To…

Optimization and Control · Mathematics 2022-04-26 Hong T. M. Chu , Ling Liang , Kim-Chuan Toh , Lei Yang

Multi-Objective Optimization (MOO) is an important problem in real-world applications. However, for a non-trivial problem, no single solution exists that can optimize all the objectives simultaneously. In a typical MOO problem, the goal is…

Machine Learning · Computer Science 2024-09-17 Zhang Haishan , Diptesh Das , Koji Tsuda

In this paper, we resolve the computational complexity of a number of outstanding open problems with practical applications. Here is the list of problems we show to be PPAD-complete, along with the domains of practical significance:…

Computational Complexity · Computer Science 2009-04-10 Shiva Kintali , Laura J. Poplawski , Rajmohan Rajaraman , Ravi Sundaram , Shang-Hua Teng

The Acceptance Probability Estimation Problem (APEP) is to additively approximate the acceptance probability of a Boolean circuit. This problem admits a probabilistic approximation scheme. A central question is whether we can design a…

Computational Complexity · Computer Science 2021-03-16 Peter Dixon , A. Pavan , N. V. Vinodchandran

The Promise Constraint Satisfaction Problem (PCSP) is a recently introduced vast generalization of the Constraint Satisfaction Problem (CSP). We investigate the computational complexity of a class of PCSPs beyond the most studied cases -…

Computational Complexity · Computer Science 2020-10-12 Libor Barto , Diego Battistelli , Kevin M. Berg

Multi-objective optimization (MOO) problems are prevalent in machine learning. These problems have a set of optimal solutions, called the Pareto front, where each point on the front represents a different trade-off between possibly…

Machine Learning · Computer Science 2021-04-27 Aviv Navon , Aviv Shamsian , Gal Chechik , Ethan Fetaya

The UNIQUE GAMES problem is a central problem in algorithms and complexity theory. Given an instance of UNIQUE GAMES, the STRONG UNIQUE GAMES problem asks to find the largest subset of vertices, such that the UNIQUE GAMES instance induced…

Data Structures and Algorithms · Computer Science 2020-05-19 Suprovat Ghoshal , Anand Louis

While discounted payoff games and classic games that reduce to them, like parity and mean-payoff games, are symmetric, their solutions are not. We have taken a fresh view on the properties that optimal solutions need to have, and devised a…

Data Structures and Algorithms · Computer Science 2026-03-11 Daniele Dell'Erba , Arthur Dumas , Sven Schewe

We consider one-round games between a classical verifier and two provers who share entanglement. We show that when the constraints enforced by the verifier are `unique' constraints (i.e., permutations), the value of the game can be well…

Quantum Physics · Physics 2009-10-03 Julia Kempe , Oded Regev , Ben Toner

It has been shown in \cite{Lan13-1} that the accelerated prox-level (APL) method and its variant, the uniform smoothing level (USL) method, have optimal iteration complexity for solving black-box and structured convex programming problems…

Optimization and Control · Mathematics 2014-12-08 Yunmei Chen , Guanghui Lan , Yuyuan Ouyang , Wei Zhang

This paper solves a new class of optimization problems under uncertainty, called Probable Event Constrained Optimization (PECO), which optimizes an objective function of decision variables and subjects to a set of Probable Event Constraints…

Optimization and Control · Mathematics 2025-03-07 Qifeng Li

The logic MMSNP is a well-studied fragment of Existential Second-Order logic that, from a computational perspective, captures finite-domain Constraint Satisfaction Problems (CSPs) modulo polynomial-time reductions. At the same time, MMSNP…

Computational Complexity · Computer Science 2026-05-12 Demian Banakh , Alexey Barsukov , Tamio-Vesa Nakajima

Continual learning aims to learn multiple tasks sequentially. A key challenge in continual learning is balancing between two objectives: retaining knowledge from old tasks (stability) and adapting to new tasks (plasticity). Experience…

Machine Learning · Computer Science 2025-04-01 Song Lai , Zhe Zhao , Fei Zhu , Xi Lin , Qingfu Zhang , Gaofeng Meng

The ever-increasing integration of stochastic renewable energy sources into power systems operation is making the supply-demand balance more challenging. While joint chance-constrained methods are equipped to model these complexities and…

Systems and Control · Electrical Eng. & Systems 2025-01-23 Meiyi Li , Javad Mohammadi

Probabilistic programming languages (PPLs) allow users to encode arbitrary inference problems, and PPL implementations provide general-purpose automatic inference for these problems. However, constructing inference implementations that are…

Programming Languages · Computer Science 2023-05-04 Daniel Lundén , Joey Öhman , Jan Kudlicka , Viktor Senderov , Fredrik Ronquist , David Broman

Covering spaces of graphs have long been useful for studying expanders (as "graph lifts") and unique games (as the "label-extended graph"). In this paper we advocate for the thesis that there is a much deeper relationship between…

Computational Complexity · Computer Science 2018-03-20 Joshua A. Grochow , Jamie Tucker-Foltz

One way of suggesting that an NP problem may not be NP-complete is to show that it is in the class UP. We suggest an analogous new approach---weaker in strength of evidence but more broadly applicable---to suggesting that concrete~NP…

Computational Complexity · Computer Science 2007-05-23 Bernd Borchert , Lane A. Hemaspaandra , Joerg Rothe

Linear and semidefinite programming (LP, SDP), regularisation through basis pursuit (BP) and Lasso have seen great success in mathematics, statistics, data science, computer-assisted proofs and learning. The success of LP is traditionally…

Optimization and Control · Mathematics 2022-08-03 Alexander Bastounis , Anders C Hansen , Verner Vlačić