AutoML Seminars

@UC3NoO2L7cGs7O3583ig--EA - 2.1K subscribers

Virtual reading group on topics about automated machine learning. For more information see: automl-seminars.github.io/

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Chronos-2: From Univariate to Universal Forecasting

Chronos-2: From Univariate to Universal Forecasting AutoML Seminars

338 views - 2 weeks ago

Stop Guessing, Start Discovering Trade-offs in Your ML Models

Stop Guessing, Start Discovering Trade-offs in Your ML Models AutoML Seminars

120 views - 1 month ago

ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution

ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution AutoML Seminars

282 views - 2 months ago

Machine Learning without data: training small models with 10 examples

Machine Learning without data: training small models with 10 examples AutoML Seminars

339 views - 2 months ago

Benchmarking Beyond Statistics: Data-Driven Footprints for Explainable Black-Box Optimization

Benchmarking Beyond Statistics: Data-Driven Footprints for Explainable Black-Box Optimization AutoML Seminars

101 views - 3 months ago

Do-PFN: In-Context Learning for Causal Effect Estimation

Do-PFN: In-Context Learning for Causal Effect Estimation AutoML Seminars

1K views - 3 months ago

Multi-Objective AutoML: Towards Accurate and Robust models

Multi-Objective AutoML: Towards Accurate and Robust models AutoML Seminars

182 views - 4 months ago

carps: A Framework for Comparing N Hyperparameter Optimizers on M Benchmarks

carps: A Framework for Comparing N Hyperparameter Optimizers on M Benchmarks AutoML Seminars

98 views - 4 months ago

Accelerating Bayesian Inference and Data Acquisition via Amortization

Accelerating Bayesian Inference and Data Acquisition via Amortization AutoML Seminars

157 views - 4 months ago

A LLM Evolutionary Algorithm for Automatically Generating Bayesian Optimization Algorithms

A LLM Evolutionary Algorithm for Automatically Generating Bayesian Optimization Algorithms AutoML Seminars

736 views - 6 months ago

TabArena: A Living Benchmark for Machine Learning on Tabular Data

TabArena: A Living Benchmark for Machine Learning on Tabular Data AutoML Seminars

568 views - 7 months ago

Tuning LLM Judge Design Decisions for 1/1000 of the Cost

Tuning LLM Judge Design Decisions for 1/1000 of the Cost AutoML Seminars

173 views - 8 months ago

Hyperband-based Bayesian Optimization for Efficient Black-box Prompt Selection

Hyperband-based Bayesian Optimization for Efficient Black-box Prompt Selection AutoML Seminars

411 views - 8 months ago

Understanding High-Dimensional Bayesian Optimization

Understanding High-Dimensional Bayesian Optimization AutoML Seminars

828 views - 9 months ago

AutoML in the Age of Structured Foundation Models

AutoML in the Age of Structured Foundation Models AutoML Seminars

543 views - 10 months ago

Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach

Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach AutoML Seminars

768 views - 11 months ago

Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization

Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization AutoML Seminars

235 views - 11 months ago

Accurate predictions on small data (and time series) with the tabular foundation model TabPFN

Accurate predictions on small data (and time series) with the tabular foundation model TabPFN AutoML Seminars

5.7K views - 1 year ago

Chronos: Time series forecasting in the age of pretrained models

Chronos: Time series forecasting in the age of pretrained models AutoML Seminars

9.2K views - 1 year ago

Scaling Exponents Across Parameterizations and Optimizers

Scaling Exponents Across Parameterizations and Optimizers AutoML Seminars

347 views - 1 year ago

Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues

Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues AutoML Seminars

617 views - 1 year ago

FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch

FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch AutoML Seminars

405 views - 1 year ago

GRAF: Performance Prediction with Neural Graph Features

GRAF: Performance Prediction with Neural Graph Features AutoML Seminars

136 views - 1 year ago

Large Language Models to Enhance Bayesian Optimization

Large Language Models to Enhance Bayesian Optimization AutoML Seminars

693 views - 1 year ago

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery AutoML Seminars

2K views - 1 year ago

einspace: Searching for Neural Architectures from Fundamental Operations

einspace: Searching for Neural Architectures from Fundamental Operations AutoML Seminars

460 views - 1 year ago

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

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

134 views - 1 year ago

Vanilla Bayesian Optimization Performs Great in High Dimensions

Vanilla Bayesian Optimization Performs Great in High Dimensions AutoML Seminars

7.6K views - 1 year ago

Multi-objective Differentiable Neural Architecture Search

Multi-objective Differentiable Neural Architecture Search AutoML Seminars

463 views - 1 year ago

Neural Fine-Tuning Search for Few-Shot Learning

Neural Fine-Tuning Search for Few-Shot Learning AutoML Seminars

249 views - 1 year ago

Is Mamba Capable of In-Context Learning?

Is Mamba Capable of In-Context Learning? AutoML Seminars

569 views - 1 year ago

Sebastian Pineda - Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How

Sebastian Pineda - Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How AutoML Seminars

2.5K views - 1 year ago

Xingyou (Richard) Song - OmniPred: Towards Universal Regressors with Language Models

Xingyou (Richard) Song - OmniPred: Towards Universal Regressors with Language Models AutoML Seminars

751 views - 1 year ago

Nick Erickson - AutoGluon 1.0: Shattering the SOTA with Zeroshot-HPO & Dynamic Stacking

Nick Erickson - AutoGluon 1.0: Shattering the SOTA with Zeroshot-HPO & Dynamic Stacking AutoML Seminars

513 views - 2 years ago

Rhea Sukthanker and Samuel Dooley - Rethinking Bias Mitigation

Rhea Sukthanker and Samuel Dooley - Rethinking Bias Mitigation AutoML Seminars

213 views - 2 years ago

Andreas Mueller - MotherNet: A Foundational Hypernetwork for Tabular Classification

Andreas Mueller - MotherNet: A Foundational Hypernetwork for Tabular Classification AutoML Seminars

678 views - 2 years ago

Arkadiy Dushatskiy: Multi-Objective Population Based Training

Arkadiy Dushatskiy: Multi-Objective Population Based Training AutoML Seminars

152 views - 2 years ago

LLMs for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering

LLMs for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering AutoML Seminars

643 views - 2 years ago

No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models

No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models AutoML Seminars

271 views - 2 years ago

Theresa Eimer: "Challenges in Hyperparameter Optimization for Reinforcement Learning"

Theresa Eimer: "Challenges in Hyperparameter Optimization for Reinforcement Learning" AutoML Seminars

269 views - 2 years ago

Alina Selega: "MO-BO with heuristic objectives for biomedical and molecular data analysis workflows"

Alina Selega: "MO-BO with heuristic objectives for biomedical and molecular data analysis workflows" AutoML Seminars

161 views - 2 years ago

Discovering Black-Box Optimizers via Evolutionary Meta-Learning

Discovering Black-Box Optimizers via Evolutionary Meta-Learning AutoML Seminars

866 views - 2 years ago

Nicholas Roberts, Samuel Guo, Cong Xu: "AutoML Decathlon Challenge"

Nicholas Roberts, Samuel Guo, Cong Xu: "AutoML Decathlon Challenge" AutoML Seminars

126 views - 2 years ago

Carola Doerr: "Hyperparameter optim. & algorithm configuration from a black-box optim. perspective"

Carola Doerr: "Hyperparameter optim. & algorithm configuration from a black-box optim. perspective" AutoML Seminars

360 views - 2 years ago

Richard Song: "Open Source Vizier"

Richard Song: "Open Source Vizier" AutoML Seminars

364 views - 2 years ago

Kartik Chandra / Audrey Xie: "Gradient Descent: The Ultimate Optimizer"

Kartik Chandra / Audrey Xie: "Gradient Descent: The Ultimate Optimizer" AutoML Seminars

686 views - 3 years ago

Subho Mukherjee: "AutoMoE: Neural Architecture Search for Efficient Sparsely Activated Transformers"

Subho Mukherjee: "AutoMoE: Neural Architecture Search for Efficient Sparsely Activated Transformers" AutoML Seminars

195 views - 3 years ago

Lisa Dunlap | "Hyperparameter Tuning on the Cloud"

Lisa Dunlap | "Hyperparameter Tuning on the Cloud" AutoML Seminars

195 views - 3 years ago

Łukasz Dudziak | "Challenges of federated and zero-cost NAS"

Łukasz Dudziak | "Challenges of federated and zero-cost NAS" AutoML Seminars

198 views - 3 years ago

Xingchen Wan | "Bayesian Generational Population-Based Training"

Xingchen Wan | "Bayesian Generational Population-Based Training" AutoML Seminars

245 views - 3 years ago

Jiaming Song | "A General Recipe for Likelihood-free Bayesian Optimization"

Jiaming Song | "A General Recipe for Likelihood-free Bayesian Optimization" AutoML Seminars

723 views - 3 years ago

Mohamed Abdelfattah | "Fast and Hardware-Aware Neural Architecture Search"

Mohamed Abdelfattah | "Fast and Hardware-Aware Neural Architecture Search" AutoML Seminars

1.7K views - 3 years ago

Yutian Chen | "Towards Learning Universal Hyperparameter Optimizers with Transformers"

Yutian Chen | "Towards Learning Universal Hyperparameter Optimizers with Transformers" AutoML Seminars

476 views - 3 years ago

Samuel Mueller | "PFNs: Use neural networks for 100x faster Bayesian predictions"

Samuel Mueller | "PFNs: Use neural networks for 100x faster Bayesian predictions" AutoML Seminars

7.3K views - 3 years ago

Greg Yang - "Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer"

Greg Yang - "Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer" AutoML Seminars

2.4K views - 3 years ago

Zi Wang | "Pre-training helps Bayesian optimization too"

Zi Wang | "Pre-training helps Bayesian optimization too" AutoML Seminars

592 views - 3 years ago

Antonio Carta | "Avalanche: an End-to-End Library for Continual Learning"

Antonio Carta | "Avalanche: an End-to-End Library for Continual Learning" AutoML Seminars

972 views - 3 years ago

Martin Wistuba | "Few-Shot Bayesian Optimization with Deep Kernel Surrogates"

Martin Wistuba | "Few-Shot Bayesian Optimization with Deep Kernel Surrogates" AutoML Seminars

272 views - 3 years ago

Ruohan Wang | "Global labels and few-shot learning"

Ruohan Wang | "Global labels and few-shot learning" AutoML Seminars

73 views - 3 years ago

David Salinas|"Syne Tune: A Library for Large-Scale Hyperparameter Tuning and Reproducible Research"

David Salinas|"Syne Tune: A Library for Large-Scale Hyperparameter Tuning and Reproducible Research" AutoML Seminars

196 views - 3 years ago