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Adi Botea

4 accepted papers

2022

Bandit Limited Discrepancy Search and Application to Machine Learning Pipeline Optimization

AAAI 2022technical

Optimizing a machine learning (ML) pipeline has been an important topic of AI and ML. Despite recent progress, pipeline optimization remains a challenging problem, due to potentially many combinations to consider as well as slow training and validation. We present the BLDS algorithm for optimized al…

Cited by 7SourcePDFScholar
2021

Searching for Machine Learning Pipelines Using a Context-Free Grammar

AAAI 2021technical

AutoML automatically selects, composes and parameterizes machine learning algorithms into a workflow or pipeline of operations that aims at maximizing performance on a given dataset. Although current methods for AutoML achieved impressive results they mostly concentrate on optimizing fixed linear wo…

2019

Depth-First Proof-Number Search with Heuristic Edge Cost and Application to Chemical Synthesis Planning

NeurIPS 2019poster

Search techniques, such as Monte Carlo Tree Search (MCTS) and Proof-Number Search (PNS), are effective in playing and solving games. However, the understanding of their performance in industrial applications is still limited. We investigate MCTS and Depth-First Proof-Number (DFPN) Search, a PNS va…

Cited by 73SourcePDFScholar
2015

Parallel Recursive Best-First AND/OR Search for Exact MAP Inference in Graphical Models

NeurIPS 2015poster

The paper presents and evaluates the power of parallel search for exact MAP inference in graphical models. We introduce a new parallel shared-memory recursive best-first AND/OR search algorithm, called SPRBFAOO, that explores the search space in a best-first manner while operating with restricted me…

Cited by 4SourcePDFScholar