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#Neural Architecture Search

Showing: 49 courses
Stanford University

Federated Hyperparameter Tuning - Challenges, Baselines, and Connections

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Explores challenges and solutions for hyperparameter tuning in federated learning, introducing FedEx method to accelerate the process. Connects to weight-sharing in neural architecture search and demonstrates improved accuracy on benchmarks.
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25 Lesons
57 minutes
On-Demand
Free-Video
Santa Fe Institute

Embodiment Without Situatedness - An Embodied Perspective on Neural Architecture Search

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Explore embodied perspectives on neural architecture search with Nick Cheney, examining the intersection of neurorobotics and complex systems in AI development and intelligence research.
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1 Lesons
35 minutes
On-Demand
Free-Video
MIT HAN Lab

MCUNet and TinyML - Lecture 10

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Explore MCUNet and TinyML for efficient machine learning on microcontrollers. Learn optimization techniques and real-world applications in resource-constrained environments.
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1 Lesons
1 hour 7 minutes
On-Demand
Free-Video
Computational Genomics Summer Institute CGSI

Training Highly Generalizable Biomedical Image Segmentation Models with Very Few Annotations

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Learn highly generalizable biomedical image segmentation techniques using minimal annotations, focusing on efficient model training and performance optimization for medical imaging tasks.
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1 Lesons
28 minutes
On-Demand
Free-Video
Yannic Kilcher

Synthetic Petri Dish - A Novel Surrogate Model for Rapid Architecture Search

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Explore a novel approach to Neural Architecture Search using a Synthetic Petri Dish model, which evaluates architectural motifs in small networks with synthetic data to accelerate performance prediction and optimization.
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10 Lesons
33 minutes
On-Demand
Free-Video
tinyML

Using AI to Design Energy-Efficient AI Accelerators for the Edge

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Explore AI-driven co-design of neural networks and hardware accelerators for edge devices, optimizing accuracy and efficiency through simultaneous architecture and hardware space exploration.
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25 Lesons
32 minutes
On-Demand
Free-Video
Aleksa Gordić - The AI Epiphany

EfficientNetV2 - Smaller Models and Faster Training - Paper Explained

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Explore EfficientNetV2's improved image classification performance, including progressive training, Fused-MBConv layer, and novel reward function for Neural Architecture Search.
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7 Lesons
28 minutes
On-Demand
Free-Video
Yannic Kilcher

Parameter Prediction for Unseen Deep Architectures - With First Author Boris Knyazev

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Explore parameter prediction for neural networks using graph hypernetworks. Learn about DeepNets-1M dataset, training techniques, and experimental results for efficient network training paradigms.
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13 Lesons
48 minutes
On-Demand
Free-Video
Yannic Kilcher

Neural Architecture Search Without Training - Paper Explained

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Explores a novel approach to Neural Architecture Search using statistics of the Jacobian around data points, enabling rapid architecture evaluation without training and significantly accelerating the search process.
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9 Lesons
35 minutes
On-Demand
Free-Video
Open Data Science

Learning to Optimize High Dimensional Optimization Problems

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Explore deep neural networks and reinforcement learning for solving high-dimensional optimization problems, improving performance in job scheduling, neural architecture search, and black-box optimization.
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19 Lesons
43 minutes
On-Demand
Free-Video
tinyML

TinyML Talks - Software-Hardware Co-design for Tiny AI Systems

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Explore efficient AI models, hardware-friendly compression, and topology-aware design for resource-constrained systems. Learn cross-optimization techniques and distributed learning for scalable AI solutions.
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36 Lesons
1 hour 2 minutes
On-Demand
Free-Video
tinyML

Putting AI on a Diet: TinyML and Efficient Deep Learning

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Efficient deep learning techniques for deploying AI on resource-constrained devices, including model compression, neural architecture search, and new design primitives for various applications.
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13 Lesons
33 minutes
On-Demand
Free-Video
tinyML

The Model Efficiency Pipeline: Enabling Deep Learning Inference at the Edge

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Explore optimizing deep learning for edge devices through model efficiency techniques, including neural architecture search, pruning, quantization, and conditional processing.
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42 Lesons
50 minutes
On-Demand
Free-Video
Linux Foundation

Hyperparameter Tuning Using Kubeflow

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Explore automated machine learning with Katib, a Kubernetes-native platform for hyperparameter tuning and neural architecture search, enhancing model performance efficiently.
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21 Lesons
35 minutes
On-Demand
Free-Video
Society for Industrial and Applied Mathematics

A Bregman Learning Framework for Sparse Neural Networks

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Explore a novel Bregman learning framework for training sparse neural networks, featuring LinBreg, momentum-accelerated, and AdaBreg algorithms, with applications in Neural Architecture Search.
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1 Lesons
1 hour 3 minutes
On-Demand
Free-Video
CNCF [Cloud Native Computing Foundation]

AutoML and Training Working Group Updates - Kubeflow Developments

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Explore AutoML and Training Working Group updates for Kubeflow, including Katib's V1 API graduation, advanced parameter distribution, and LLM tuning, plus Training Operator's roadmap for enhanced ML framework support.
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1 Lesons
36 minutes
On-Demand
Free-Video
Center for Language & Speech Processing(CLSP), JHU

Neural Architecture Search: Coming of Age

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Explore Neural Architecture Search advancements, including benchmarks, speedup techniques, AutoML integration, and neural ensemble search. Gain insights from a leading expert in automated machine learning.
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1 Lesons
58 minutes
On-Demand
Free-Video
WeAreDevelopers

Deep Learning for Mobile Devices

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Strategies for implementing efficient convolutional neural networks on mobile devices, covering model optimization, hardware considerations, and on-device training techniques.
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22 Lesons
44 minutes
On-Demand
Free-Video
MIT HAN Lab

TinyML and Efficient Deep Learning Computing - Course Summary

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Explore efficient machine learning techniques for deploying neural networks on resource-constrained devices, covering model compression, pruning, quantization, and more.
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3 Lesons
13 minutes
On-Demand
Free-Video
MIT HAN Lab

TinyML and Efficient Deep Learning Computing - Lecture 24: Course Summary

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Explore efficient machine learning techniques for deploying neural networks on resource-constrained devices. Gain hands-on experience with mobile AI and quantum machine learning.
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1 Lesons
13 minutes
On-Demand
Free-Video
Yannic Kilcher

SpineNet - Learning Scale-Permuted Backbone for Recognition and Localization

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Explores SpineNet, a novel CNN architecture using scale-permuted features and cross-scale connections, outperforming traditional models in object detection and classification tasks.
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11 Lesons
36 minutes
On-Demand
Free-Video
AutoML Seminars

AutoMoE - Neural Architecture Search for Efficient Sparsely Activated Transformers

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Discover how Neural Architecture Search optimizes Transformer models through sparse activation, achieving 4x FLOP reduction while maintaining performance in machine translation tasks.
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1 Lesons
47 minutes
On-Demand
Free-Video
AutoML Seminars

Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face-Recognition

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Explore groundbreaking research on addressing bias in face recognition systems through neural architecture optimization, revealing how architectural choices impact fairness more than data preprocessing alone.
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1 Lesons
41 minutes
On-Demand
Free-Video
AutoML Seminars

Neural Fine-Tuning Search for Few-Shot Learning

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Explore advanced neural architecture search techniques for optimizing few-shot learning adaptation strategies, focusing on meta-training and meta-testing trade-offs in multi-domain contexts.
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1 Lesons
30 minutes
On-Demand
Free-Video
AutoML Seminars

Multi-objective Differentiable Neural Architecture Search

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Explore advanced techniques in neural architecture optimization across multiple objectives and hardware devices, focusing on Pareto front profiling and hypernetwork-based solutions.
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1 Lesons
43 minutes
On-Demand
Free-Video
AutoML Seminars

Mixture-of-Supernets - Improving Weight-Sharing Supernet Training with Architecture-Routed MoE

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Explore cutting-edge research on Mixture-of-Supernets architecture that enhances neural architecture search efficiency and improves BERT and MT model performance through innovative weight-sharing techniques.
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1 Lesons
35 minutes
On-Demand
Free-Video
AutoML Seminars

Searching for Neural Architectures from Fundamental Operations - An Introduction to einspace

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Explore neural architecture search through einspace, a novel approach using fundamental operations to discover diverse and competitive network architectures for machine learning tasks.
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1 Lesons
38 minutes
On-Demand
Free-Video
Toronto Machine Learning Series (TMLS)

AutoML Towards Deep Learning: Optimizing Neural Architectures and Hyperparameters

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Explore advances in AutoML for Deep Learning, focusing on joint optimization, efficiency, and robustness. Learn about the future of automated neural architecture and hyperparameter optimization.
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1 Lesons
57 minutes
On-Demand
Free-Video
MIT HAN Lab

AI Model Efficiency Toolkit (AIMET) - Lecture 25

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Explore AI model efficiency techniques with Qualcomm's toolkit. Learn about adaptive rounding, autocon, and transformer quantization for optimized inference and training on resource-constrained devices.
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17 Lesons
45 minutes
On-Demand
Free-Video
MIT HAN Lab

AI Model Efficiency Toolkit (AIMET) - Lecture 25

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Explore AI model efficiency techniques with Qualcomm AI Research. Learn about AIMET, community research, core technologies, and industry applications for optimizing deep learning models.
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21 Lesons
45 minutes
On-Demand
Free-Video
MIT HAN Lab

Neural Architecture Search (Part II) - Lecture 8

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Explore neural architecture search techniques, including hardware-aware approaches and joint optimization of hardware and neural architectures. Learn applications and advancements in efficient deep learning design.
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1 Lesons
1 hour 13 minutes
On-Demand
Free-Video
MIT HAN Lab

Neural Architecture Search for Efficient Deep Learning - Lecture 9

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Explore advanced neural architecture search techniques for efficient deep learning on resource-constrained devices. Gain insights into model optimization for mobile and IoT applications.
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1 Lesons
1 hour 7 minutes
On-Demand
Free-Video
MIT HAN Lab

Neural Architecture Search (Part II) - Lecture 8

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Explore neural architecture search techniques, including hardware-aware approaches and joint optimization of hardware and neural architectures. Learn applications and advancements in efficient deep learning design.
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1 Lesons
1 hour 13 minutes
On-Demand
Free-Video
VinAI

Functional Gradient Descent Methods for Optimization and Sampling

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Explore advanced gradient descent techniques for complex optimization and sampling problems in machine learning, including Stein variational gradient descent and neural architecture optimization.
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1 Lesons
1 hour 3 minutes
On-Demand
Free-Video
MIT HAN Lab

Quantum Machine Learning - Lecture 22

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Explore quantum machine learning fundamentals, bridging quantum computing and AI. Gain insights into this emerging field's potential to revolutionize computational approaches.
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1 Lesons
1 hour 9 minutes
On-Demand
Free-Video
MIT HAN Lab

Efficient Transformers - Lecture 20

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Explore efficient transformer architectures for optimized deep learning on resource-constrained devices. Learn techniques to enhance performance and reduce computational demands.
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1 Lesons
1 hour 18 minutes
On-Demand
Free-Video
MIT HAN Lab

Efficient Transformers - Lecture 20

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Explore efficient transformer architectures for optimized deep learning on resource-constrained devices. Learn techniques to enhance performance and reduce computational demands.
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1 Lesons
1 hour 18 minutes
On-Demand
Free-Video
AutoML Seminars

Challenges of Federated and Zero-Cost Neural Architecture Search

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Explore advanced neural architecture search techniques, focusing on federated settings and zero-cost searching algorithms through weight sharing and efficient subnet discovery methods.
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1 Lesons
1 hour 2 minutes
On-Demand
Free-Video
MIT HAN Lab

Neural Architecture Search - Part I

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Explore neural architecture search techniques, focusing on automated design of efficient deep learning models for various applications.
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1 Lesons
1 hour 14 minutes
On-Demand
Free-Video
MIT HAN Lab

Neural Architecture Search - Part I (EfficientML.ai) - Lecture 7

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Explore neural architecture search techniques for optimizing deep learning models, covering fundamentals, methods, and applications in AI efficiency.
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1 Lesons
1 hour 14 minutes
On-Demand
Free-Video
MIT HAN Lab

Neural Architecture Search - Part II - Lecture 8

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Explore advanced neural architecture search techniques, including gradient-based methods and hardware-aware NAS, to optimize deep learning models for efficiency and performance.
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1 Lesons
1 hour 15 minutes
On-Demand
Free-Video
MIT HAN Lab

Neural Architecture Search (Part II) - Lecture 8

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Explore advanced neural architecture search techniques, including evolutionary algorithms and reinforcement learning, to optimize deep learning models for efficiency and performance.
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1 Lesons
1 hour 15 minutes
On-Demand
Free-Video
MIT HAN Lab

Neural Architecture Search Part I - Lecture 7

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Explore neural architecture search techniques for optimizing deep learning models, covering fundamental concepts and cutting-edge approaches in AI efficiency.
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1 Lesons
1 hour 6 minutes
On-Demand
Free-Video
MIT HAN Lab

Neural Architecture Search Part I - Lecture 7

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Explore neural architecture search techniques for optimizing deep learning models, focusing on automated design and efficiency in AI systems.
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1 Lesons
1 hour 6 minutes
On-Demand
Free-Video
MIT HAN Lab

Neural Architecture Search Part II - Lecture 8

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Explore advanced neural architecture search techniques, including evolutionary algorithms and reinforcement learning, to optimize deep learning models for efficiency and performance.
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1 Lesons
1 hour 16 minutes
On-Demand
Free-Video
MIT HAN Lab

Neural Architecture Search Part II - Lecture 8

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Explore advanced neural architecture search techniques, including evolutionary algorithms and reinforcement learning for optimizing deep learning models.
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1 Lesons
1 hour 16 minutes
On-Demand
Free-Video
Center for Language & Speech Processing(CLSP), JHU

Efficient Language Models - Tutorial

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Explore efficient language model techniques with JHU researcher Tianjian Li, covering optimization strategies and cutting-edge approaches for improved NLP performance.
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1 Lesons
1 hour 7 minutes
On-Demand
Free-Video
Scalable Parallel Computing Lab, SPCL @ ETH Zurich

Democratizing Deep Learning with DeepHyper

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Explore DeepHyper: Automate DNN design for scientific data using scalable neural architecture and hyperparameter search. Learn to generate DNN ensembles for uncertainty estimation in various applications.
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4 Lesons
1 hour 1 minute
On-Demand
Free-Video
Center for Language & Speech Processing(CLSP), JHU

AutoML for Natural Language Processing - EACL 2013 Tutorial

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Explore AutoML techniques for NLP, covering hyperparameter optimization and neural architecture search to improve model-building rigor and efficiency.
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1 Lesons
2 hours 44 minutes
On-Demand
Free-Video