Search Results for author: Ryan Williams

Found 8 papers, 2 papers with code

Reframing the Mind-Body Picture: Applying Formal Systems to the Relationship of Mind and Matter

no code implementations11 Apr 2024 Ryan Williams

This paper aims to show that a simple framework, utilizing basic formalisms from set theory and category theory, can clarify and inform our theories of the relation between mind and matter.

Relation

Real-Time Systems Optimization with Black-box Constraints and Hybrid Variables

no code implementations21 Jan 2024 Sen Wang, Dong Li, Shao-Yu Huang, Xuanliang Deng, Ashrarul H. Sifat, Changhee Jung, Ryan Williams, Haibo Zeng

When optimizing real-time systems, designers often face a challenging problem where the schedulability constraints are non-convex, non-continuous, or lack an analytical form to understand their properties.

A General and Scalable Method for Optimizing Real-Time Systems

no code implementations6 Jan 2024 Sen Wang, Dong Li, Shao-Yu Huang, Xuanliang Deng, Ashrarul H. Sifat, Changhee Jung, Ryan Williams, Haibo Zeng

In real-time systems optimization, designers often face a challenging problem posed by the non-convex and non-continuous schedulability conditions, which may even lack an analytical form to understand their properties.

Optimizing Logical Execution Time Model for Both Determinism and Low Latency

no code implementations30 Oct 2023 Sen Wang, Dong Li, Ashrarul H. Sifat, Shao-Yu Huang, Xuanliang Deng, Changhee Jung, Ryan Williams, Haibo Zeng

Therefore, fLET has the potential to significantly improve the end-to-end timing performance while keeping the benefits of deterministic behavior on timing and dataflow.

MAJORITY-3SAT (and Related Problems) in Polynomial Time

no code implementations6 Jul 2021 Shyan Akmal, Ryan Williams

For the closely related GtMajority-SAT problem (where we ask whether a given formula has greater than $2^{n-1}$ satisfying assignments) which is known to be PP-complete, we show that GtMajority-$k$SAT is in P for $k\le 3$, but becomes NP-complete for $k\geq 4$.

Learning Multi-Agent Communication through Structured Attentive Reasoning

1 code implementation NeurIPS 2020 Murtaza Rangwala, Ryan Williams

Learning communication via deep reinforcement learning has recently been shown to be an effective way to solve cooperative multi-agent tasks.

Decision Making Multi-agent Reinforcement Learning +3

Super-Linear Gate and Super-Quadratic Wire Lower Bounds for Depth-Two and Depth-Three Threshold Circuits

no code implementations24 Nov 2015 Daniel M. Kane, Ryan Williams

$\bullet$ We give tight average-case (gate and wire) complexity results for computing PARITY with depth-two threshold circuits; the answer turns out to be the same as for depth-two majority circuits.

LEMMA

Faster all-pairs shortest paths via circuit complexity

1 code implementation23 Dec 2013 Ryan Williams

On the word RAM, the algorithm runs in $n^3/2^{\Omega(\log n)^{1/2}} + n^{2+o(1)}\log M$ time for edge weights in $([0, M] \cap {\mathbb Z})\cup\{\infty\}$.

Data Structures and Algorithms Computational Complexity Combinatorics

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