Results 61 to 70 of about 1,259,133 (314)

The Natural Language Decathlon: Multitask Learning as Question Answering [PDF]

, 2018
Presented on August 28, 2018 at 12:15 p.m. in the Pettit Microelectronics Research Center, Room 102 A/B.Bryan McCann is a Senior Research Scientist at Salesforce.
McCann, Bryan
core  

GADMM : Fast and Communication Efficient Framework for Distributed Machine Learning [PDF]

, 2020
When the data is distributed across multiple servers, lowering the communication cost between the servers (or workers) while solving the distributed learning problem is an important problem and is the focus of this paper. In particular, we propose a fast,
Bedi, Amrit S., Aggarwal, Vaneet, Bennis, Mehdi, Elgabli, Anis, Park, Jihong   +4 more
core  

A Euclidean transformer for fast and stable machine learned force fields

Nature Communications
Recent years have seen vast progress in the development of machine learned force fields (MLFFs) based on ab-initio reference calculations. Despite achieving low test errors, the reliability of MLFFs in molecular dynamics (MD) simulations is facing ...
J. Thorben Frank, Oliver T. Unke, Klaus-Robert Müller, Stefan Chmiela   +3 more
doaj   +1 more source

Epigenetic heterogeneity and plasticity in therapy‐induced tumor states through single‐cell multi‐omics

Molecular Oncology, EarlyView.
Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim, Hwiyeong Lee, Jin Hong, Daechan Park   +3 more
wiley   +1 more source

Pairwise meta-rules for better meta-learning-based algorithm ranking [PDF]

, 2013
In this paper, we present a novel meta-feature generation method in the context of meta-learning, which is based on rules that compare the performance of individual base learners in a one-against-one manner.
Pfahringer, Bernhard, Sun, Quan
core   +1 more source

From tumor‐centric to ecosystem‐based hypotheses in brain tumor research and care

Molecular Oncology, EarlyView.
Primary brain tumors, whether in adults or children, present a major challenge because of their dramatic prognosis and the ongoing lack of efficient therapeutic approaches. In recent years, a shift has occurred from tumor‐centric concepts to a more holistic view of these tumors as dynamic ecosystems.
Julie Gavard, Flavie Bénard, Eva Billat, Margaux Le Guyon, Victoria Maltret, Laura Merlet, Chloé Astrid Walter, Tony Avril, Eric Chevet   +8 more
wiley   +1 more source

Monitoring the lactation-related behaviors of sows and their piglets in farrowing crates using deep learning

Frontiers in Animal Science
Pig farming is a major sector of livestock production. The preweaning stage is a critical period in the pig farming process, where lactation-related behaviors between sows and their piglets directly influence the preweaning survivability of the piglets ...
Yu-Jung Tsai, Yi-Che Huang, En-Chung Lin, Sheng-Chieh Lai, Xu-Chu Hong, Jonas Tsai, Cheng-En Chiang, Yan-Fu Kuo   +7 more
doaj   +1 more source

MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning

Entropy, 2019
Efficient approximation lies at the heart of large-scale machine learning problems. In this paper, we propose a novel, robust maximum entropy algorithm, which is capable of dealing with hundreds of moments and allows for computationally efficient ...
Diego Granziol, Binxin Ru, Stefan Zohren, Xiaowen Dong, Michael Osborne, Stephen Roberts   +5 more
doaj   +1 more source

Single‐cell DNA methylation profiling: Technologies, computation, and applications in precision oncology

Molecular Oncology, EarlyView.
Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley   +1 more source

Qudit machine learning

Machine Learning: Science and Technology
Abstract We present a comprehensive investigation into the learning capabilities of a simple d-level system (qudit). Our study is specialized for classification tasks using real-world databases, specifically the Iris, breast cancer, and MNIST datasets.
Sebastián Roca-Jerat, Juan Román-Roche, David Zueco   +2 more
openaire   +6 more sources