Results 111 to 120 of about 476,790 (313)
Provable Representation Learning for Imitation Learning via Bi-level Optimization
, 2020 A common strategy in modern learning systems is to learn a representation that is useful for many tasks, a.k.a. representation learning. We study this strategy in the imitation learning setting for Markov decision processes (MDPs) where multiple experts’
Arora, Sanjeev +4 more
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Knowledge Representation for Adaptive Learning Design [PDF]
, 2006 Please, cite this publication as: Kravcik, M. & Gasevic, D. (2006). Knowledge Representation for Adaptive Learning Design. Proceedings of Adaptive Hypermedia. June, Dublin, Ireland.
Gasevic, Dragan, Kravcik, Milos
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, 2021 Recent studies have been demonstrated that the excessive inflammatory response is an important factor of death in COVID-19 patients. In this study, we proposed a network representation learning-based methodology, termed AIdrug2cov, to discover drug ...
Fei, Li +7 more
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Long‐Term Follow‐Up of Chemotherapy‐Associated Biological Aging in Women With Early Breast Cancer
Aging and Cancer, EarlyView.Women threated with adjuvant chemotherapy for early breast cancer have sustained long‐term increase in p16INK4a,, a robust marker of cell senescence, suggesting a chemotherapy‐associated age acceleration. p16INK4a as well as other biomarkers may identify patients at greatest risk for senescence‐related diseases of aging.
Hyman B. Muss +12 more
wiley +1 more source
Learning Action Representations for Reinforcement Learning
CoRR, 2019 Most model-free reinforcement learning methods leverage state representations (embeddings) for generalization, but either ignore structure in the space of actions or assume the structure is provided a priori. We show how a policy can be decomposed into a component that acts in a low-dimensional space of action representations and a component that ...
Yash Chandak +4 more
openaire +3 more sources
Editorial: Multimodal communication and multimodal computing
Frontiers in Artificial Intelligence, 2023 Alexander Mehler +3 more
doaj +1 more source
Self-supervised video representation learning
, 2023 Videos are an appealing source of data to train computer vision models. There exist almost infinite supplies of videos online, but exhaustive manual annotation is infeasible.
Han, Tengda
core +1 more source
Aging and Cancer, EarlyView.This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel +4 more
wiley +1 more source
Few-Shot Fine-Grained Image Classification: A Comprehensive Review
AIFew-shot fine-grained image classification (FSFGIC) methods refer to the classification of images (e.g., birds, flowers, and airplanes) belonging to different subclasses of the same species by a small number of labeled samples.
Jie Ren +4 more
doaj +1 more source