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#Domain Adaptation

Showing: 43 courses
Massachusetts Institute of Technology

Introduction to Deep Learning

12 rewiews
Deep Learning is subset of machine learning focused on extracting patterns from data using neural networks and use those patterns to inform the learning tasks.
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71 Lesons
2 days 7 hours 16 minutes
On-Demand
Free-Video
Stanford University

Style Transfer Augmentations for Computational Pathology - Rikiya Yamashita

0 rewiews
Innovative style transfer augmentation technique for improving machine learning model generalization in computational pathology, enhancing robustness to domain shifts and achieving state-of-the-art performance in classification tasks.
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27 Lesons
52 minutes
On-Demand
Free-Video
Stanford University

Domain Adaptation with Invariant Representation Learning - What Transformations to Learn?

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Explore domain adaptation in machine learning, focusing on invariant representation learning and its challenges. Learn about novel techniques for optimal feature mapping across domains.
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14 Lesons
58 minutes
On-Demand
Free-Video
Stanford University

Divide and Conquer - Concept-based Models for Efficient Transfer Learning

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Exploring concept-based interpretable AI models for efficient transfer learning in healthcare, focusing on generalizability and minimal data requirements for domain adaptation in medical imaging.
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1 Lesons
1 hour
On-Demand
Free-Video
Yale University

Improved Ultrasound Image Formation - Domain Adaptation With No Data

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Explore advanced techniques for enhancing ultrasound imaging through domain adaptation, focusing on methods that require no additional data input.
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1 Lesons
24 minutes
On-Demand
Free-Video
University of Central Florida

One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning

0 rewiews
Learn domain-adaptive meta-learning for one-shot imitation, enabling robots to quickly learn new tasks by observing human demonstrations and adapting across domains.
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16 Lesons
30 minutes
On-Demand
Free-Video
University of Central Florida

Statistical and Spatial Consensus Collection for Detector Adaption

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Explore detector adaptation techniques for improved pedestrian detection across domains, focusing on statistical and spatial consensus methods to enhance accuracy and generalization.
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21 Lesons
51 minutes
On-Demand
Free-Video
University of Central Florida

Geo-localization Framework for Real-world Scenarios - Defense Presentation

0 rewiews
Explore advanced geo-localization techniques using vision transformers and novel loss functions for improved accuracy in real-world scenarios, with a focus on bridging domain gaps.
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21 Lesons
39 minutes
On-Demand
Free-Video
MLOps World: Machine Learning in Production

Enhance Cost Efficiency in Domain Adaptation with PruneMe

0 rewiews
Optimize LLMs through layer pruning, enabling cost-effective domain adaptation and model merging for improved performance in specific applications.
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1 Lesons
17 minutes
On-Demand
Free-Video
Simons Institute

Controlling Distribution Shifts in Language Models: A Data-Centric Approach

0 rewiews
Explore data-centric approaches to control distribution shifts in language models, focusing on algorithmic filtering and domain-specific data synthesis for improved generalization.
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1 Lesons
1 hour 5 minutes
On-Demand
Free-Video
Simons Institute

What is Your Data Worth? Equitable Data Valuation in Machine Learning

0 rewiews
Explore equitable data valuation in machine learning, focusing on Data Shapley Value and its applications in healthcare, face recognition, and NLP.
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18 Lesons
44 minutes
On-Demand
Free-Video
Association for Computing Machinery (ACM)

Learning Transferable Human Behavior Representations From Sensor Data - Flora Salim

0 rewiews
Explore techniques for learning transferable human behavior representations from sensor data, including challenges, preprocessing, and applications in various domains.
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14 Lesons
44 minutes
On-Demand
Free-Video
Discover AI

Domain-Specific AI Models - Creating Customized BERT and SBERT Models for Business Applications

0 rewiews
Discover how to effectively train and fine-tune BERT and SBERT models for specialized domains, focusing on medical and biochemical terminology, with practical solutions for business applications.
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6 Lesons
12 minutes
On-Demand
Free-Video
Simons Institute

Measures of Relatedness in Domain Adaptation and Related Problems

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Explore unstructured distribution shifts, discrepancy measures, and adaptation techniques in domain adaptation and transfer learning settings.
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1 Lesons
1 hour 15 minutes
On-Demand
Free-Video
Bolei Zhou

Responsible Computer Vision - Model Failures and Solutions

0 rewiews
Explore visual recognition challenges, dataset biases, and domain adaptation techniques to improve model performance and address fairness issues in computer vision systems.
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24 Lesons
55 minutes
On-Demand
Free-Video
Graham Neubig

Neural Nets for NLP 2017 - Multilingual and Multitask Learning

0 rewiews
Explore multitask, domain adaptation, and multilingual learning in neural networks for NLP. Gain insights into feature extraction, data augmentation, and cross-lingual techniques for improved language processing.
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19 Lesons
52 minutes
On-Demand
Free-Video
Elvis Saravia

Sentiment Analysis - Key Milestones, Challenges and New Directions

0 rewiews
Explore key milestones, challenges, and new directions in sentiment analysis, covering topics from polarity detection to multimodal analysis and sentiment reasoning.
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13 Lesons
1 hour 17 minutes
On-Demand
Free-Video
Simons Institute

Machine Learning-Based Design of Proteins and Small Molecules

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Explore machine learning techniques for designing proteins and small molecules, covering directed evolution, model-based optimization, and challenges in deep learning applications.
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22 Lesons
46 minutes
On-Demand
Free-Video
Simons Institute

Robust Deep Learning Under Distribution Shift

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Explore deep learning challenges under distribution shift, covering adversarial attacks, label shift detection, and domain adaptation techniques for robust model performance in real-world scenarios.
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33 Lesons
50 minutes
On-Demand
Free-Video
Open Data Science

Learning with Limited Labels - ODSC West 2020

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Explore advanced techniques for machine learning with limited labeled data, including domain adaptation, few-shot learning, and self-supervised learning to enhance model performance across diverse domains and novel categories.
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11 Lesons
40 minutes
On-Demand
Free-Video
tinyML

Learning Compact Representation with Less Labeled Data from Sensors

0 rewiews
Exploring data-efficient learning techniques for compact representations in sensor-based human behavior modeling, focusing on domain adaptation and pretraining approaches for minimal labeled data scenarios.
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13 Lesons
27 minutes
On-Demand
Free-Video
Andreas Geiger

Making Our Models Robust to Changing Visual Environments

0 rewiews
Explore techniques for making machine learning models robust to changing visual environments, covering domain adaptation, adversarial optimization, and continuous learning strategies.
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26 Lesons
46 minutes
On-Demand
Free-Video
Computational Genomics Summer Institute CGSI

Divide and Conquer: Carving Out Symbolic Models from BlackBox for More Efficient Domain Adaptation

0 rewiews
Explore techniques for extracting symbolic models from black-box systems, enhancing domain adaptation efficiency in computational genomics and medical imaging.
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14 Lesons
32 minutes
On-Demand
Free-Video
SK AI SUMMIT 2024

RAG vs PEFT - Comparing LLM Domain Adaptation Methods

0 rewiews
Delve into LLM 도메인 적용을 위한 RAG와 PEFT 방식의 비교 분석과 SK브로드밴드의 실제 구현 사례를 통한 AWS 환경 구축 및 모델 개발 노하우
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1 Lesons
24 minutes
On-Demand
Free-Video
Snorkel AI

Why GenAI Needs Careful Training Data Management

0 rewiews
Explore the critical role of training data management in GenAI, including harmonization across stages and its impact on model effectiveness and safety in various domains and languages.
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1 Lesons
18 minutes
On-Demand
Free-Video
Snorkel AI

When, Why and How to Fine-Tune LLMs for Enterprise Applications

0 rewiews
Explore techniques for customizing large language models in enterprise settings, including when and why to align LLMs and key methods for domain-specific adaptation.
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1 Lesons
18 minutes
On-Demand
Free-Video
GOTO Conferences

Covariate Shift - Challenges and Good Practice in Machine Learning

0 rewiews
Explore challenges and best practices in covariate shift, a crucial concept in machine learning, with insights on improving model performance and adaptability in changing data distributions.
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1 Lesons
21 minutes
On-Demand
Free-Video
Stanford University

Large Scale Multi-Microscope Datasets and Their Challenges in Medical AI

0 rewiews
Explore groundbreaking research on multi-microscope datasets for malaria and leukemia detection, featuring innovative domain adaptation techniques and object detection methods to enhance early disease diagnosis.
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1 Lesons
56 minutes
On-Demand
Free-Video
Alexander Amini

Taming Dataset Bias via Domain Adaptation

0 rewiews
Explore techniques to address dataset bias in deep learning, including adversarial domain alignment, pixel space alignment, and consistency enforcement for improved model generalization.
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10 Lesons
43 minutes
On-Demand
Free-Video
VinAI

Domain Adaptation on Wheels: Closing the Gap to the Open-world

0 rewiews
Explore domain adaptation techniques for autonomous driving, from standard unsupervised setups to practical approaches addressing open-world challenges in semantic segmentation and scene understanding.
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1 Lesons
1 hour 16 minutes
On-Demand
Free-Video
Simons Institute

Domain Adaptation - 20 Years of Theory Chasing Practice

0 rewiews
Explore the evolving relationship between theoretical frameworks and practical applications in domain adaptation learning, examining key insights, challenges, and the widening theory-practice gap.
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1 Lesons
37 minutes
On-Demand
Free-Video
Simons Institute

Domain Adaptation and Related Areas in Machine Learning

0 rewiews
Dive into domain adaptation concepts and related machine learning areas with Carnegie Mellon expert Zachary Lipton, exploring theoretical frameworks and practical applications.
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1 Lesons
43 minutes
On-Demand
Free-Video
Simons Institute

Adaptive Data Collection via Autoregressive Generation in News Recommendation Systems

0 rewiews
Discover how autoregressive models can enhance adaptive data collection and decision-making through Thompson sampling, with applications in news recommendation systems and cold-start problems.
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1 Lesons
45 minutes
On-Demand
Free-Video
Simons Institute

Toward Understanding the Extrapolation of Nonlinear Models to Unseen Domains

0 rewiews
Explore advanced concepts in domain adaptation and model extrapolation, focusing on nonlinear models' behavior in unseen domains through theoretical and practical analysis.
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1 Lesons
42 minutes
On-Demand
Free-Video
Simons Institute

Language-Guided Domain Adaptation

0 rewiews
Explore cutting-edge techniques in domain adaptation and language-guided methods with UC Berkeley expert Trevor Darrrell, focusing on advanced machine learning applications and methodologies.
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1 Lesons
52 minutes
On-Demand
Free-Video
Simons Institute

Causally Motivated Robustness to Shortcut Learning in Machine Learning

0 rewiews
Delve into techniques for building robust machine learning models that maintain performance under distribution shifts, with a focus on preventing shortcut learning through causal regularization methods.
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1 Lesons
45 minutes
On-Demand
Free-Video
Simons Institute

Pseudo-Labeling for Covariate Shift Adaptation in Machine Learning

0 rewiews
Explore advanced covariate shift adaptation techniques using pseudo-labeling methods for regression tasks, focusing on kernel ridge regression and bias-variance optimization for target distributions.
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1 Lesons
39 minutes
On-Demand
Free-Video
Simons Institute

The Evolution of Domain Transfer in the Era of Pre-trained Language Models

0 rewiews
Explore the complex relationship between pre-trained language models and domain transfer, examining how pre-training affects model understanding and pattern recognition across different contexts.
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1 Lesons
43 minutes
On-Demand
Free-Video
Simons Institute

The Data Addition Dilemma: Navigating Distribution Shifts in Machine Learning

0 rewiews
Explore the complexities of combining data sources in machine learning, examining when adding more data helps or hurts model performance and fairness across different distributions.
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1 Lesons
37 minutes
On-Demand
Free-Video
Simons Institute

Distribution Shift in Ecological Data - Generalization vs. Specialization

0 rewiews
Explore the balance between general and specific computer vision approaches for ecological challenges, focusing on data shifts, adaptation methods, and real-world applications.
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1 Lesons
41 minutes
On-Demand
Free-Video
Simons Institute

Transfer Learning via Local Convergence Rates of the Nonparametric Least Squares Estimator

0 rewiews
Explore nonparametric least squares estimator's local convergence properties and their implications for transfer learning under covariate shift, focusing on weighted uniform norm optimization.
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1 Lesons
41 minutes
On-Demand
Free-Video
Simons Institute

Transfer Learning for Weak-to-Strong Generalization in Language Model Alignment

0 rewiews
Explore how to effectively transfer latent knowledge from weak to strong language models, focusing on alignment techniques and practical applications in LLM development.
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1 Lesons
42 minutes
On-Demand
Free-Video
Simons Institute

A Discrepancy-Based Theory of Domain Adaptation

0 rewiews
Delve into domain adaptation theory through discrepancy concepts, exploring sample reweighting techniques and algorithmic applications for robust machine learning solutions.
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1 Lesons
54 minutes
On-Demand
Free-Video