Main Track
Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues Inproceedings In: Proceedings of the Thirteenth International Conference on Learning Representations (ICLR), 2025, (Oral). |
Efficient Cross-Episode Meta-RL Inproceedings In: Proceedings of the Thirteenth International Conference on Learning Representations (ICLR'25), 2025. |
KinPFN: Bayesian Approximation of RNA Folding Kinetics using Prior-Data Fitted Networks Inproceedings In: Proceedings of the Thirteenth International Conference on Learning Representations (ICLR), 2025. |
Diffusion-based Neural Network Weights Generation Inproceedings In: Proceedings of the Thirteenth International Conference on Learning Representations (ICLR), 2025. |
Beyond Random Augmentations: Pretraining with Hard Views Conference Proceedings of the Thirteenth International Conference on Learning Representations (ICLR), 2025. |
TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks Inproceedings In: 38th Conference on Neural Information Processing Systems (NeurIPS), 2024. |
Improving Deep Learning Optimization through Constrained Parameter Regularization Inproceedings In: 38th Conference on Neural Information Processing Systems (NeurIPS), 2024. |
Drift-Resilient TabPFN: In-Context Learning Distribution Shifts on Tabular Data Inproceedings In: 38th Conference on Neural Information Processing Systems (NeurIPS), 2024. |
A Human-in-the-Loop Fairness-Aware Model Selection Framework for Complex Fairness Objective Landscapes Inproceedings In: Proceedings of the Seventh AAAI/ACM Conference on AI, Ethics, and Society (AIES-24), 2024. |
HPO-RL-Bench: A Zero-Cost Benchmark for HPO in Reinforcement Learning Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), ABCD Track, 2024, (Runner up for the best paper award). |
Weight-Entanglement Meets Gradient-Based Neural Architecture Search Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Methods Track, 2024. |
Is Mamba Capable of In-Context Learning? Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Methods Track, 2024. |
TabRepo: A Large Scale Repository of Tabular Model Evaluations and its AutoML Applications Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), ABCD Track, 2024. |
Fast Benchmarking of Asynchronous Multi-Fidelity Optimization on Zero-Cost Benchmarks Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), ABCD Track, 2024. |
Don’t Waste Your Time: Early Stopping Cross-Validation Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Methods Track, 2024. |
Surprisingly Strong Performance Prediction with Neural Graph Features Inproceedings In: Proceedings of the 41st International Conference on Machine Learning (ICML), 2024. |
In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization Inproceedings In: Proceedings of the 41st International Conference on Machine Learning (ICML), 2024. |
Position: A Call to Action for a Human-Centered AutoML Paradigm Inproceedings In: Proceedings of the 41st International Conference on Machine Learning (ICML), 2024. |
A General Framework for User-Guided Bayesian Optimization Inproceedings In: The Twelfth International Conference on Learning Representations (ICLR), 2024. |
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How Inproceedings In: The Twelfth International Conference on Learning Representations (ICLR), 2024, (Oral Presentation). |
Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars Inproceedings In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023. |
Self-Correcting Bayesian Optimization through Bayesian Active Learning Inproceedings In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023. |
Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition Inproceedings In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023, (Oral Paper - top 2% of accepted papers). |
PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning Inproceedings In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023. |
Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks Inproceedings In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023. |
Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering Inproceedings In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023. |
Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design Inproceedings In: Oh, Alice H.; Agarwal, Alekh; Belgrave, Danielle; Cho, Kyunghyun (Ed.): Advances in Neural Information Processing Systems (NeurIPS 2022), 2022. |
Joint Entropy Search For Maximally-Informed Bayesian Optimization Inproceedings In: Oh, Alice H.; Agarwal, Alekh; Belgrave, Danielle; Cho, Kyunghyun (Ed.): Advances in Neural Information Processing Systems (NeurIPS 2022), 2022. |
Datasets and Benchmarks Track
HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models Inproceedings In: 38th Conference on Neural Information Processing Systems (NeurIPS), DBT Track, 2024. |
JAHS-Bench-201: A Foundation For Research On Joint Architecture And Hyperparameter Search Inproceedings In: Thirty-sixth Conference on Neural Information Processing Systems, 2022, (Featured Paper - top 7.5% of accepted papers). |
NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies Inproceedings In: Thirty-sixth Conference on Neural Information Processing Systems, 2022. |
Workshops
One-shot World Models Using a Transformer Trained on a Synthetic Prior Inproceedings In: NeurIPS 2024 Workshop on Open-World Agents, 2024. |
Large Language Models Engineer Too Many Simple Features for Tabular Data Inproceedings In: NeurIPS 2024 Third Table Representation Learning Workshop, 2024, (Oral Presentation). |
Ensembling Finetuned Language Models for Text Classification Inproceedings In: NeurIPS 2024 Workshop on Fine-Tuning in Modern Machine Learning: Principles and Scalability, 2024. |
Warmstarting for Scaling Language Models Inproceedings In: NeurIPS 2024 Workshop Adaptive Foundation Models, 2024. |
Mamba4Cast: Efficient Zero-Shot Time Series Forecasting with State Space Models Inproceedings In: NeurIPS 2024 TSALM Workshop, 2024, (Spotlight Presentation). |
Large Language Model Compression with Neural Architecture Search Inproceedings In: NeurIPS 2024 Workshop on Machine Learning and Compression, 2024. |
GAMformer: Exploring In-Context Learning for Generalized Additive Models Inproceedings In: NeurIPS 2024 TRL Workshop, 2024. |
The Tabular Foundation Model TabPFN Outperforms Specialized Time Series Forecasting Models Based on Simple Features Inproceedings In: NeurIPS 2024 TRL Workshop, 2024. |
Unlocking State-Tracking in linear RNNs through Negative Eigenvalues Inproceedings In: NeurIPS 2024 Workshop on Mathematics of Modern Machine Learning Workshop (M3L), 2024, (Oral Presentation). |
Transfer Learning for Finetuning Large Language Models Inproceedings In: NeurIPS 2024 Workshop on Adaptive Foundation Models, 2024. |
CANDID DAC: Leveraging Coupled Action Dimensions with Importance Differences in DAC Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024. |
FairPFN: Transformers Can do Counterfactual Fairness Conference Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024. |
Towards Efficient Search for Customized Activation Functions With Gradient Descent Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024. |
LMEMs for post-hoc analysis of HPO Benchmarking Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024. |
Quick-Tune-Tool: A Practical Tool and its User Guide for Automatically Finetuning Pretrained Models Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024. |
NOSBench-101: Towards Reproducible Neural Optimizer Search Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024. |
Drift-Resilient TabPFN: In-Context Learning Distribution Shifts on Tabular Data Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024. |
In-Context Learning for Latency Estimation Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024. |
LoRA-DARTS: Low Rank Adaptation for Differentiable Architecture Search Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024. |
In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024. |
From Epoch to Sample Size: Developing New Data-driven Priors for Learning Curve Prior-Fitted Networks Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024. |
Beyond Graph-Based Modeling for Hierarchical Neural Architecture Search Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024. |
Fast Optimizer Benchmark Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024. |
Hardware Aware Ensemble Selection for Balancing Predictive Accuracy and Cost Inproceedings In: Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, 2024. |
Multi-objective Differentiable Neural Architecture Search Conference 2nd Workshop on Advancing Neural Network Training: Computational Efficiency, Scalability, and Resource Optimization (WANT@ICML), 2024. |
CoordConformer: Heterogenous EEG datasets decoding using Transformers Conference Workshop on Geometry-grounded Representation Learning and Generative Modeling (GRaM@ICML), 2024. |
RNA-Protein Interaction Prediction via Sequence Embeddings Workshop The Generative and Experimental perspectives in bioMolecular design (GEM) workshop (ICLR 2024), 2024. |
Towards Generative RNA Design with Tertiary Interactions Workshop The Generative and Experimental perspectives in bioMolecular design (GEM) workshop (ICLR 2024), 2024, (Oral Presentation). |
Towards Quantifying the Effect of Datasets for Benchmarking: A Look at Tabular Machine Learning Inproceedings In: Data-centric Machine Learning Research (DMLR) Workshop (ICLR 2024), 2024. |
Preserving Principal Subspaces to Reduce Catastrophic Forgetting in Fine-tuning Inproceedings In: Mathematical and Empirical Understanding of Foundation Models (ME-FoMo) Workshop, 2024. |
Is Mamba Capable of In-Context Learning? Inproceedings In: Mathematical and Empirical Understanding of Foundation Models (ME-FoMo) Workshop, 2024. |
Rethinking Performance Measures of RNA Secondary Structure Problems Workshop Machine Learning for Structural Biology Workshop, (NeruIPS 2023), 2023. |
New Horizons in Parameter Regularization: A Constraint Approach Inproceedings In: OPT2023: 15th Annual Workshop on Optimization for Machine Learning, (NeurIPS 2023), 2023. |
AutoRL-Bench 1.0 Inproceedings In: Workshop on Meta-Learning (MetaLearn@NeurIPS'22), 2022. |
Gray-Box Gaussian Processes for Automated Reinforcement Learning Inproceedings In: Workshop on Meta-Learning (MetaLearn@NeurIPS'22), 2022. |
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second Inproceedings In: NeurIPS 2022 First Table Representation Workshop, 2022. |
Bayesian Optimization with a Neural Network Meta-learned on Synthetic Data Only Workshop Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022. |
Towards Discovering Neural Architectures from Scratch Inproceedings In: Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022. |
Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks Inproceedings In: Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022. |
GraViT-E: Gradient-based Vision Transformer Search with Entangled Weights Inproceedings In: Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022. |
Multi-objective Tree-structured Parzen Estimator Meets Meta-learning Inproceedings In: Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022. |
PriorBand: HyperBand + Human Expert Knowledge Inproceedings In: Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022. |
On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition Inproceedings In: Workshop on Trustworthy and Socially Responsible Machine Learning, NeurIPS 2022, 2022. |
On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition Inproceedings In: Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022. |
Transfer NAS with Meta-learned Bayesian Surrogates Inproceedings In: Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022. |
In: NeurIPS Workshop on Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems, 2022. |