https://www.amazon.science/publications/automatic-table-union-search-with-tabular-representation-learning
Automatic table union search with tabular representation learning - Amazon Science
Given a data lake of tabular data as well as a query table, how can we retrieve all the tables in the data lake that can be unioned with the query table? Table...
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https://www.amazon.science/tag/multitask-learning
Multitask learning - Amazon Science
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https://www.amazon.science/publications/client-private-secure-aggregation-for-privacy-preserving-federated-learning
Client-private secure aggregation for privacy preserving federated learning - Amazon Science
Privacy-preserving federated learning (PPFL) is a paradigm of distributed privacy-preserving machine learning training in which a set of clients, each holding...
federated learningclientprivatesecureaggregation
https://www.amazon.science/publications/knowledge-distillation-for-large-language-models-through-residual-learning
Knowledge distillation for large language models through residual learning - Amazon Science
Knowledge distillation has become a crucial technique to transfer the capacities of large language models (LLMs) to smaller, more efficient models for...
large language modelsknowledge distillationlearning amazon
https://www.amazon.science/publications/an-inductive-bias-for-tabular-deep-learning
An inductive bias for tabular deep learning - Amazon Science
Deep learning methods have achieved state-of-the-art performance in most modeling tasks involving images, text and audio, however, they typically underperform...
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https://www.amazon.science/publications/acoustic-model-bootstrapping-using-semi-supervised-learning
Acoustic Model Bootstrapping Using Semi-Supervised Learning - Amazon Science
This work aims at bootstrapping the acoustic model training with small amount of the human annotated speech data and large amount of the unlabeled speech data...
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https://www.amazon.science/publications/vision-language-pre-training-with-triple-contrastive-learning
Vision-language pre-training with triple contrastive learning - Amazon Science
Vision-language representation learning largely benefits from image-text alignment through contrastive losses (e.g., InfoNCE loss). The success of this...
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https://www.amazon.science/publications/federated-multi-objective-learning
Federated multi-objective learning - Amazon Science
In recent years, multi-objective optimization (MOO) emerges as a foundational problem underpinning many multi-agent multi-task learning applications. However,...
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https://www.amazon.science/publications/generalization-and-robustness-implications-in-object-centric-learning
Generalization and robustness implications in object-centric learning - Amazon Science
The idea behind object-centric representation learning is that natural scenes can better be modeled as compositions of objects and their relations as opposed...
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https://www.amazon.science/publications/language-agnostic-multilingual-information-retrieval-with-contrastive-learning
Language agnostic multilingual information retrieval with contrastive learning - Amazon Science
Multilingual information retrieval (IR) is challenging since annotated training data is costly to obtain in many languages. We present an effective method to...
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https://www.amazon.science/tag/deep-learning
Deep learning - Amazon Science
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https://www.amazon.science/publications/bridging-the-gap-to-real-world-object-centric-learning
Bridging the gap to real-world object-centric learning - Amazon Science
Humans naturally decompose their environment into entities at the appropriate level of abstraction to act in the world. Allowing machine learning algorithms to...
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https://www.amazon.science/code-and-datasets/meta-q-learning
Meta-Q-Learning - Amazon Science
This paper introduces Meta-Q-Learning (MQL), a new off-policy algorithm for meta-Reinforcement Learning (meta-RL). MQL builds upon three simple ideas. First,...
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https://www.amazon.science/tag/active-learning
Active learning - Amazon Science
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https://www.amazon.science/publications/a-quantile-based-approach-for-hyperparameter-transfer-learning
A quantile-based approach for hyperparameter transfer learning - Amazon Science
Bayesian optimization (BO) is a popular methodology to tune the hyperparameters of expensive black-box functions. Despite its success, standard BO focuses on a...
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https://www.amazon.science/publications/fr-lora-fisher-regularized-lora-for-multilingual-continual-learning
FR-LoRA: Fisher regularized LoRA for multilingual continual learning - Amazon Science
Relevance in e-commerce product search is critical to ensuring that results accurately reflect customer intent. While large language models (LLMs) have...
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https://www.amazon.science/publications/fedmultimodal-a-benchmark-for-multimodal-federated-learning
FedMultimodal: A benchmark for multimodal federated learning - Amazon Science
Over the past few years, Federated Learning (FL) has become an emerging machine learning technique to tackle data privacy challenges through collaborative...
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https://www.amazon.science/blog/why-ambient-computing-needs-self-learning
Why ambient computing needs self-learning - Amazon Science
Nov 14, 2024 - To become the interface for the Internet of things, conversational agents will need to learn on their own. Alexa has already started down that path.
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https://www.amazon.science/tag/transfer-learning
Transfer learning - Amazon Science
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https://www.amazon.science/blog/more-reliable-nearest-neighbor-search-with-deep-metric-learning/
More reliable nearest-neighbor search with deep metric learning - Amazon Science
May 31, 2024 - Novel loss term that can be added to any loss function regularizes interclass and intraclass distances.
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https://www.amazon.science/publications/data-augmentation-for-supervised-code-translation-learning
Data augmentation for supervised code translation learning - Amazon Science
Data-driven program translation has been recently the focus of sev- eral lines of research. A common and robust strategy is supervised learning. However, there...
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https://www.amazon.science/academic-engagements/usc-amazon-center-on-secure-and-trusted-machine-learning-selects-initial-research-projects
USC + Amazon Center on Secure and Trusted Machine Learning selects initial research projects -...
Oct 22, 2025 - Innovative faculty proposals will explore various aspects of trustworthy machine learning.
https://leanpub.com/amazonmachinelearning-anintroduction
Amazon Machine Learning [Leanpub PDF/iPad/Kindle]
amazon machine learning, machine learning, supervised learning, regression, binary classification, multi class classification
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https://www.amazon.science/publications/video-contrastive-learning-with-global-context
Video contrastive learning with global context - Amazon Science
Contrastive learning has revolutionized the self-supervised image representation learning field and recently been adapted to the video domain. One of the...
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https://www.amazon.science/publications/when-do-minimax-fair-learning-and-empirical-risk-minimization-coincide
When do minimax-fair learning and empirical risk minimization coincide? - Amazon Science
Minimax-fair machine learning minimizes the error for the worst-off group. However, empirical evidence suggests that when sophisticated models are trained with...
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https://www.mediapost.com/publications/article/318465/amazon-alexa-google-assistant-a-learning-experie.html
Amazon Alexa, Google Assistant: A Learning Experience 05/01/2018
Amazon Alexa, Google Assistant: A Learning Experience - 05/01/2018
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https://www.reed.co.uk/courses/amazon-web-services-aws-solution-architect-professional/224944?itm_source=js_search_results&itm_medium=jobseeker&itm_campaign=keyword_search_courses_panel&itm_content=Architect_courses_224944
Online Amazon Web Services - AWS - Solution Architect Professional Course - Learning People |...
Take this Amazon Web Services - AWS - Solution Architect Professional course and gain essential IT skills today. Advance your career prospects with Reed...
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https://www.amazon.science/publications/sava-scalable-learning-agnostic-data-valuation
SAVA: Scalable learning-agnostic data valuation - Amazon Science
Selecting data for training machine learning models is crucial since large, web-scraped, real datasets contain noisy artifacts that affect the quality and...
data valuationsavascalablelearningagnostic
https://www.amazon.jobs/en/jobs/10388266/senior-applied-scientist-international-machine-learning?cmpid=bsp-amazon-science
Senior Applied Scientist, International Machine Learning - Job ID: 10388266 | Amazon.jobs
Explore corporate jobs and career programs at Amazon, from full-time roles to internships. Join our global teams and create a better future for our customers.
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https://www.amazon.science/publications/leveraging-sparse-and-shared-feature-activations-for-disentangled-representation-learning
Leveraging sparse and shared feature activations for disentangled representation learning - Amazon...
Research on recovering the latent factors of variation of high dimensional data has so far focused on simple synthetic settings. Mostly building on...
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