H. Samulowitz

发表

An effective algorithm for hyperparameter optimization of neural networks

Achille Fokoue, Giacomo Nannicini, Horst Samulowitz, 2017, IBM J. Res. Dev..

Learning Feature Engineering for Classification

Deepak S. Turaga, Udayan Khurana, Horst Samulowitz, 2017, IJCAI.

Peter J. Stuckey, Tom Schrijvers, Horst Samulowitz, 2012, LOPSTR.

Image inpainting through neural networks hallucinations

Pascal Frossard, Deepak S. Turaga, Horst Samulowitz, 2016, 2016 IEEE 12th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP).

Human-AI Collaboration in Data Science

Parikshit Ram, Michael Muller, Horst Samulowitz, 2019, Proc. ACM Hum. Comput. Interact..

Algorithm Portfolios Based on Cost-Sensitive Hierarchical Clustering

Yuri Malitsky, Meinolf Sellmann, Ashish Sabharwal, 2013, IJCAI.

Survey on Automated End-to-End Data Science?

Parikshit Ram, Charu Aggarwal, Udayan Khurana, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

How can AI Automate End-to-End Data Science? pdf

Charu C. Aggarwal, Parikshit Ram, Alexander G. Gray, 2019, ArXiv.

AutoAI-TS: AutoAI for Time Series Forecasting

Wesley M. Gifford, Syed Yousaf Shah, Xuan-Hong Dang, 2021, SIGMOD Conference.

How Much Automation Does a Data Scientist Want? pdf

Soya Park, Udayan Khurana, Horst Samulowitz, 2021, ArXiv.

Adaptive data augmentation for image classification

Pascal Frossard, Deepak S. Turaga, Horst Samulowitz, 2016, 2016 IEEE International Conference on Image Processing (ICIP).

NeuNetS: An Automated Synthesis Engine for Neural Network Design pdf

Rong Yan, Constantine Bekas, Benjamin Herta, 2019, ArXiv.

Algorithm Selection and Scheduling

Yuri Malitsky, Serdar Kadioglu, Meinolf Sellmann, 2011, CP.

Model-Based Genetic Algorithms for Algorithm Configuration

Yuri Malitsky, Carlos Ansótegui, Meinolf Sellmann, 2015, IJCAI.

Deep Learning for Algorithm Portfolios

Yuri Malitsky, Vijay A. Saraswat, Horst Samulowitz, 2016, AAAI.

Cognito: Automated Feature Engineering for Supervised Learning

Deepak S. Turaga, Udayan Khurana, Horst Samulowitz, 2016, 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW).

Feature Engineering for Predictive Modeling using Reinforcement Learning

Deepak S. Turaga, Udayan Khurana, Horst Samulowitz, 2017, AAAI.

Parallel SAT Solver Selection and Scheduling

Yuri Malitsky, Meinolf Sellmann, Ashish Sabharwal, 2012, CP.

Automated Data Science for Relational Data

Udayan Khurana, Horst Samulowitz, Tran Ngoc Minh, 2021, 2021 IEEE 37th International Conference on Data Engineering (ICDE).

Guiding Combinatorial Optimization with UCT

Ashish Sabharwal, Horst Samulowitz, Chandra Reddy, 2012, CPAIOR.

Using SAT in QBF

Fahiem Bacchus, Horst Samulowitz, F. Bacchus, 2005, CP.

Experiments with Massively Parallel Constraint Solving

Lucas Bordeaux, Horst Samulowitz, Youssef Hamadi, 2009, IJCAI.

Deep Learning for Cost-Optimal Planning: Task-Dependent Planner Selection

Shirin Sohrabi, Horst Samulowitz, Michael Katz, 2019, AAAI.

A Vision for Semantically Enriched Data Science

Kavitha Srinivas, Udayan Khurana, Sainyam Galhotra, 2023, ArXiv.

A Survey on Semantics in Automated Data Science

Kavitha Srinivas, Horst Samulowitz, Udayan Khurana, 2022, ArXiv.

An ADMM Based Framework for AutoML Pipeline Configuration

Alexander G. Gray, A. Conn, Sijia Liu, 2019, AAAI.

Selecting Near-Optimal Learners via Incremental Data Allocation pdf

Gerald Tesauro, Ashish Sabharwal, Horst Samulowitz, 2015, AAAI.

With contributions from

Peter James Stuckey, L. Koninck, Horst Samulowitz, 1992 .

Learning Back-Clauses in SAT - (Poster Presentation)

Meinolf Sellmann, Ashish Sabharwal, Horst Samulowitz, 2012, SAT.

LakeBench: Benchmarks for Data Discovery over Data Lakes

I. Abdelaziz, Kavitha Srinivas, Tejaswini Pedapati, 2023, ArXiv.

Cognitive Automation of Data Science

Horst Samulowitz, Chandra Reddy, Ashish Sabharwal, 2014 .