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Electronic Colloquium on Computational Complexity

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REPORTS > AUTHORS > NOAH FLEMING:
All reports by Author Noah Fleming:

TR24-185 | 21st November 2024
Susanna F. de Rezende, Noah Fleming, Duri Andrea Janett, Jakob Nordström, Shuo Pang

Truly Supercritical Trade-offs for Resolution, Cutting Planes, Monotone Circuits, and Weisfeiler-Leman

We exhibit supercritical trade-off for monotone circuits, showing that there are functions computable by small circuits for which any circuit must have depth super-linear or even super-polynomial in the number of variables, far exceeding the linear worst-case upper bound. We obtain similar trade-offs in proof complexity, where we establish the ... more >>>


TR24-178 | 5th November 2024
Noah Fleming, Yuichi Yoshida

Sensitivity Lower Bounds for Approximaiton Algorithms

Sensitivity measures how much the output of an algorithm changes, in terms of Hamming distance, when part of the input is modified. While approximation algorithms with low sensitivity have been developed for many problems, no sensitivity lower bounds were previously known for approximation algorithms. In this work, we establish the ... more >>>


TR24-010 | 19th January 2024
Noah Fleming, Stefan Grosser, Toniann Pitassi, Robert Robere

Black-Box PPP is not Turing-Closed

Revisions: 1

The complexity class PPP contains all total search problems many-one reducible to the PIGEON problem, where we are given a succinct encoding of a function mapping n+1 pigeons to n holes, and must output two pigeons that collide in a hole. PPP is one of the “original five” syntactically-defined subclasses ... more >>>


TR23-052 | 19th April 2023
Noah Fleming, Vijay Ganesh, Antonina Kolokolova, Chunxiao Li, Marc Vinyals

Limits of CDCL Learning via Merge Resolution

In their seminal work, Atserias et al. and independently Pipatsrisawat and Darwiche in 2009 showed that CDCL solvers can simulate resolution proofs with polynomial overhead. However, previous work does not address the tightness of the simulation, i.e., the question of how large this overhead needs to be. In this paper, ... more >>>




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