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A general guide to applying machine learning to computer architecture [PDF]
, 2018 The resurgence of machine learning since the late 1990s has been enabled by significant advances in computing performance and the growth of big data.
Arkose, Tugberk +6 more
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Discriminative Cooperative Networks for Detecting Phase Transitions [PDF]
, 2018 The classification of states of matter and their corresponding phase transitions is a special kind of machine-learning task, where physical data allow for the analysis of new algorithms, which have not been considered in the general computer-science ...
Liu, Ye-Hua +1 more
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Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy [PDF]
, 2017 Astrophysics and cosmology are rich with data. The advent of wide-area digital cameras on large aperture telescopes has led to ever more ambitious surveys of the sky.
Gieseke, Fabian +4 more
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Data Deluge in Astrophysics: Photometric Redshifts as a Template Use Case [PDF]
, 2018 Astronomy has entered the big data era and Machine Learning based methods have found widespread use in a large variety of astronomical applications. This is demonstrated by the recent huge increase in the number of publications making use of this new ...
A. J. Connolly +33 more
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Machine Learning Bell Nonlocality in Quantum Many-body Systems
, 2017 Machine learning, the core of artificial intelligence and big data science, is one of today's most rapidly growing interdisciplinary fields. Recently, its tools and techniques have been adopted to tackle intricate quantum many-body problems. In this work,
Deng, Dong-Ling
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A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems [PDF]
, 2019 We propose a set of compositional design patterns to describe a large variety of systems that combine statistical techniques from machine learning with symbolic techniques from knowledge representation.
Teije, Annette ten, van Harmelen, Frank
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Predicting Scientific Success Based on Coauthorship Networks [PDF]
, 2014 We address the question to what extent the success of scientific articles is due to social influence. Analyzing a data set of over 100000 publications from the field of Computer Science, we study how centrality in the coauthorship network differs between
Garas, Antonios +4 more
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Convex Analysis and Optimization with Submodular Functions: a Tutorial [PDF]
, 2010 Set-functions appear in many areas of computer science and applied mathematics, such as machine learning, computer vision, operations research or electrical networks.
Bach, Francis
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Pedagogical Possibilities for the N-Puzzle Problem
, 2006 In this paper we present work on a project funded by the National Science Foundation with a goal of unifying the Artificial Intelligence (AI) course around the theme of machine learning.
Markov, Zdravko +3 more
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Optimaztion of Fantasy Basketball Lineups via Machine Learning [PDF]
, 2019 Machine learning is providing a way to glean never before known insights from the data that gets recorded every day. This paper examines the application of machine learning to the novel field of Daily Fantasy Basketball.
Earl, James
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