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#Multi-Task Learning

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Stanford University

Stanford Seminar 2022 - DeepMind's Perceiver and Perceiver IO: New Data Family Architecture

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Exploring DeepMind's Perceiver architecture for flexible AI processing across diverse data types, offering domain-general solutions comparable to specialized models in various tasks.
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1 Lesons
59 minutes
On-Demand
Free-Video
Stanford University

Intuitions on Language Models and Shaping AI's Future - Stanford CS25 Lecture

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Explore intuitions on language models and the evolution of Transformer architectures with OpenAI researchers. Gain insights into next-word prediction, scaling laws, and the future of AI development.
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1 Lesons
1 hour 17 minutes
On-Demand
Free-Video
Association for Computing Machinery (ACM)

When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications - Lecture 1

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Explore parameter-efficient fine-tuning techniques for multi-task medical applications using Mixture of Experts and Large Language Models.
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1 Lesons
14 minutes
On-Demand
Free-Video
Association for Computing Machinery (ACM)

MDMTRec: An Adaptive Multi-Task Multi-Domain Recommendation Framework - SIGIR 2024

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Explore an adaptive framework for multi-task, multi-domain recommendations, enhancing personalized content suggestions across various platforms and contexts.
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1 Lesons
13 minutes
On-Demand
Free-Video
Alexander Amini

MIT 6.S191 - Deep Learning Limitations and New Frontiers

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Explore deep learning limitations, adversarial attacks, uncertainty quantification, and AutoML in this lecture. Gain insights into neural network challenges and emerging frontiers in AI research.
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24 Lesons
36 minutes
On-Demand
Free-Video
Montreal Robotics

RoboCat - A Self-Improving Generalist for Robotic Manipulation

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Explore RoboCat, a multi-embodiment, multi-task generalist agent for robotic manipulation. Learn about its ability to generalize across tasks and robots, and its potential for autonomous improvement.
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1 Lesons
45 minutes
On-Demand
Free-Video
Data Science Conference

LTV Forecasting and Churn Analysis for Mobile Gaming Revenue Optimization

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Discover advanced LTV forecasting and churn analysis techniques for mobile gaming, focusing on whale player identification, MTL neural networks, and practical implementation strategies.
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1 Lesons
24 minutes
On-Demand
Free-Video
Data Science Conference

Industry NLP: Multitask and Continual Learning - Adapters and Hypernetworks Approach

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Discover how adapters and hypernetworks revolutionize NLP tasks through multi-task and continual learning approaches, enabling faster training, efficient storage, and seamless ML system integration.
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1 Lesons
28 minutes
On-Demand
Free-Video
Yannic Kilcher

Active Dendrites Avoid Catastrophic Forgetting - Interview With the Authors

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Interview exploring how active dendrites in neural networks can mitigate catastrophic forgetting, enabling better multi-task and continual learning for AI systems in dynamic environments.
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17 Lesons
57 minutes
On-Demand
Free-Video
Yannic Kilcher

Avoiding Catastrophe - Active Dendrites Enable Multi-Task Learning in Dynamic Environments

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Explore how active dendrites in neural networks mitigate catastrophic forgetting, enabling multi-task learning and adaptation in dynamic environments through context-sensitive gating and sparse representations.
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12 Lesons
1 hour 5 minutes
On-Demand
Free-Video
Graham Neubig

Neural Nets for NLP 2019: Sentence and Contextualized Word Representations

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Explore sentence representations and contextual word embeddings for NLP tasks. Learn about multi-task learning, transfer learning, and pre-training techniques to improve model performance.
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21 Lesons
1 hour 18 minutes
On-Demand
Free-Video
Graham Neubig

Advanced NLP: Adversarial Methods for Text

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Explore advanced NLP techniques including adversarial networks, discrete outputs, and input manipulation for robust language models and applications.
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22 Lesons
1 hour 17 minutes
On-Demand
Free-Video
Graham Neubig

CMU Advanced NLP: Pre-training Methods

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Explore advanced NLP concepts including multi-task learning, sentence embeddings, BERT variants, and language modeling objectives. Gain insights into cutting-edge techniques for natural language processing.
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25 Lesons
1 hour 22 minutes
On-Demand
Free-Video
Graham Neubig

CMU Multilingual NLP 2020 - Advanced Text Classification-Labeling

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Explore advanced text classification and sequence labeling methods, including subword models, unsupervised training, and structured prediction for multilingual NLP applications.
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24 Lesons
50 minutes
On-Demand
Free-Video
Graham Neubig

CMU Neural Nets for NLP 2020 - Multitask and Multilingual Learning

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Explore multitask and multilingual learning in NLP, covering methods, objectives, and challenges. Gain insights into cross-lingual transfer, data balancing, and zero-shot approaches.
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18 Lesons
1 hour 3 minutes
On-Demand
Free-Video
Yannic Kilcher

Gradient Surgery for Multi-Task Learning

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Explore PCGrad, a technique addressing gradient conflicts in multi-task learning, enhancing efficiency and performance in supervised and reinforcement learning scenarios.
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8 Lesons
32 minutes
On-Demand
Free-Video
Yannic Kilcher

IMPALA - Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures

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Explore IMPALA, a distributed reinforcement learning architecture for efficient multi-task learning. Learn about V-trace, off-policy correction, and scalable performance across thousands of machines.
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1 Lesons
21 minutes
On-Demand
Free-Video
Discover AI

Layer Increasing Network Scaling (LiNeS) - Preventing Catastrophic Forgetting in Language Models

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Explore LiNeS, a novel post-training layer scaling technique that prevents catastrophic forgetting in large language models while enhancing multi-task performance and model merging capabilities.
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9 Lesons
21 minutes
On-Demand
Free-Video
Center for Language & Speech Processing(CLSP), JHU

Where Does Negative Transfer Come From? On the Implicit Bias of SGD in Multi-Task Learning

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Explore negative transfer in multi-task learning, examining task conflict, optimization temperature, and SGD's implicit bias. Gain insights into generalization challenges in neural networks.
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1 Lesons
29 minutes
On-Demand
Free-Video
tinyML

Next-Level Parameter Sharing - The Future of AI Collaboration

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Explore cutting-edge multi-task learning techniques for tinyML, focusing on hard contextual parameter sharing to enhance AI collaboration and efficiency in resource-constrained environments.
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1 Lesons
15 minutes
On-Demand
Free-Video
Data Science Conference

Multi-Task Learning in Transformer-Based Architectures for Natural Language Processing

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Explore multi-task learning in transformers, covering adapter techniques, hypernetworks, and efficient solutions for training multiple NLP tasks with shared architectures and reduced computational costs.
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18 Lesons
31 minutes
On-Demand
Free-Video
Center for Language & Speech Processing(CLSP), JHU

Low-resource Morphological Generation with Neural Sequence-to-Sequence Models

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Explore neural sequence-to-sequence approaches for morphological generation in low-resource languages, including multi-task learning, cross-lingual transfer, and semi-supervised techniques.
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1 Lesons
47 minutes
On-Demand
Free-Video
MLOps.community

Ads Ranking Evolution at Pinterest - From Logistic Regression to Deep Learning

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Explore Pinterest's ads ranking evolution, from logistic regression to deep learning transformers, incorporating sequential signals and multi-task learning. Gain insights on overcoming challenges and advancing ML platforms.
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18 Lesons
53 minutes
On-Demand
Free-Video
Anyscale

Large Scale Pathways Recommender Systems (PaRS) at Verizon

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Explore Verizon's innovative multi-task learning recommender system, PaRS, leveraging Ray ecosystem to enhance customer experience through deep learning and efficient large-scale model training.
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1 Lesons
31 minutes
On-Demand
Free-Video
VinAI

A View in Old and New Machine Learning

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Explore old and new machine learning approaches, comparing hierarchical probabilistic models with deep neural networks and examining their unique capabilities and potential combinations.
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1 Lesons
1 hour 33 minutes
On-Demand
Free-Video
VinAI

Generative Sequence Models for Sequential Decision Making

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Explore generative sequence models for decision-making under uncertainty. Learn how Transformer architecture and language modeling advances can enhance offline learning, online exploration, and multi-task generalization in AI.
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1 Lesons
1 hour 10 minutes
On-Demand
Free-Video