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2020 – today
- 2024
- [c63]Inwon Kang, Parikshit Ram, Yi Zhou, Horst Samulowitz, Oshani Seneviratne:
Effective Data Distillation for Tabular Datasets (Student Abstract). AAAI 2024: 23533-23534 - [c62]Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen:
Enhancing In-context Learning via Linear Probe Calibration. AISTATS 2024: 307-315 - [c61]Momin Abbas, Yi Zhou, Nathalie Baracaldo, Horst Samulowitz, Parikshit Ram, Theodoros Salonidis:
Byzantine-Resilient Bilevel Federated Learning. SAM 2024: 1-5 - [c60]Long Vu, Peter Kirchner, Charu C. Aggarwal, Horst Samulowitz:
Instance-Level Metalearning for Outlier Detection. IJCAI 2024: 2379-2387 - [c59]Daniel Karl I. Weidele, Mauro Martino, Abel N. Valente, Gaetano Rossiello, Hendrik Strobelt, Loraine Franke, Kathryn Alvero, Shayenna Misko, Robin Auer, Sugato Bagchi, Nandana Mihindukulasooriya, Md. Faisal Mahbub Chowdhury, Gregory Bramble, Horst Samulowitz, Alfio Gliozzo, Lisa Amini:
Empirical Evidence on Conversational Control of GUI in Semantic Automation. IUI 2024: 869-885 - [c58]Saket Sathe, Charu Aggarwal, Horst Samulowitz, Deepak S. Turaga:
Feature-Engineered Random Forests. SDM 2024: 100-108 - [i25]Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen:
Enhancing In-context Learning via Linear Probe Calibration. CoRR abs/2401.12406 (2024) - [i24]Jana Vatter, Ruben Mayer, Hans-Arno Jacobsen, Horst Samulowitz, Michael Katz:
Choosing a Classical Planner with Graph Neural Networks. CoRR abs/2402.04874 (2024) - [i23]Md. Ibrahim Ibne Alam, Parikshit Ram, Soham Dan, Horst Samulowitz, Koushik Kar:
On the Utility of Domain-Adjacent Fine-Tuned Model Ensembles for Few-shot Problems. CoRR abs/2406.13720 (2024) - [i22]Aamod Khatiwada, Harsha Kokel, Ibrahim Abdelaziz, Subhajit Chaudhury, Julian Dolby, Oktie Hassanzadeh, Zhenhan Huang, Tejaswini Pedapati, Horst Samulowitz, Kavitha Srinivas:
TabSketchFM: Sketch-based Tabular Representation Learning for Data Discovery over Data Lakes. CoRR abs/2407.01619 (2024) - 2023
- [j5]Ibrahim Abdelaziz, Julian Dolby, Udayan Khurana, Horst Samulowitz, Kavitha Srinivas:
DataRinse: Semantic Transforms for Data preparation based on Code Mining. Proc. VLDB Endow. 16(12): 4090-4093 (2023) - [c57]Pranav Subramaniam, Udayan Khurana, Kavitha Srinivas, Horst Samulowitz:
NumJoin: Discovering Numeric Joinable Tables with Semantically Related Columns. CIKM 2023: 5096-5100 - [c56]Pranav Subramaniam, Udayan Khurana, Kavitha Srinivas, Horst Samulowitz:
Related Table Search for Numeric data using Large Language Models and Enterprise Knowledge Graphs. EKG-LLM@CIKM 2023 - [c55]Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig:
Single-shot General Hyper-parameter Optimization for Federated Learning. ICLR 2023 - [c54]Ibrahim Abdelaziz, Julian Dolby, Udayan Khurana, Horst Samulowitz, Kavitha Srinivas:
SemFORMS: Automatic Generation of Semantic Transforms By Mining Data Science Code. IJCAI 2023: 7106-7109 - [c53]Elita A. Lobo, Oktie Hassanzadeh, Nhan Pham, Nandana Mihindukulasooriya, Dharmashankar Subramanian, Horst Samulowitz:
Matching table metadata with business glossaries using large language models. OM@ISWC 2023: 25-36 - [c52]Parikshit Ram, Alexander G. Gray, Horst C. Samulowitz, Gregory Bramble:
Toward Theoretical Guidance for Two Common Questions in Practical Cross-Validation based Hyperparameter Selection. SDM 2023: 802-810 - [c51]Daniel Karl I. Weidele, Gaetano Rossiello, Gregory Bramble, Abel N. Valente, Sugato Bagchi, Md. Faisal Mahbub Chowdhury, Mauro Martino, Nandana Mihindukulasooriya, Haritha Ananthakrishnan, Hendrik Strobelt, Hima Patel, Alfio Massimiliano Gliozzo, Owen Cornec, Ankush Gupta, Sameep Mehta, Manish Kesarwani, Horst Samulowitz, Oktie Hassanzadeh, Arvind Agarwal, Lisa Amini:
Conversational GUI for Semantic Automation Layer. ISWC (Posters/Demos/Industry) 2023 - [c50]Md. Ibrahim Ibne Alam, Koushik Kar, Theodoros Salonidis, Horst Samulowitz:
FLASH: Automating federated learning using CASH. UAI 2023: 45-55 - [i21]Parikshit Ram, Alexander G. Gray, Horst C. Samulowitz, Gregory Bramble:
Toward Theoretical Guidance for Two Common Questions in Practical Cross-Validation based Hyperparameter Selection. CoRR abs/2301.05131 (2023) - [i20]Udayan Khurana, Kavitha Srinivas, Sainyam Galhotra, Horst Samulowitz:
A Vision for Semantically Enriched Data Science. CoRR abs/2303.01378 (2023) - [i19]Kavitha Srinivas, Julian Dolby, Ibrahim Abdelaziz, Oktie Hassanzadeh, Harsha Kokel, Aamod Khatiwada, Tejaswini Pedapati, Subhajit Chaudhury, Horst Samulowitz:
LakeBench: Benchmarks for Data Discovery over Data Lakes. CoRR abs/2307.04217 (2023) - [i18]Elita A. Lobo, Oktie Hassanzadeh, Nhan Pham, Nandana Mihindukulasooriya, Dharmashankar Subramanian, Horst Samulowitz:
Matching Table Metadata with Business Glossaries Using Large Language Models. CoRR abs/2309.11506 (2023) - 2022
- [c49]Kavitha Srinivas, Takaaki Tateishi, Daniel Karl I. Weidele, Udayan Khurana, Horst Samulowitz, Toshihiro Takahashi, Dakuo Wang, Lisa Amini:
Semantic Feature Discovery with Code Mining and Semantic Type Detection. AAAI 2022: 13224-13226 - [i17]Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig:
Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm & Analysis. CoRR abs/2202.08338 (2022) - [i16]Udayan Khurana, Kavitha Srinivas, Horst Samulowitz:
A Survey on Semantics in Automated Data Science. CoRR abs/2205.08018 (2022) - 2021
- [c48]Arunima Chaudhary, Alayt Issak, Kiran Kate, Yannis Katsis, Abel N. Valente, Dakuo Wang, Alexandre V. Evfimievski, Sairam Gurajada, Ban Kawas, A. Cristiano I. Malossi, Lucian Popa, Tejaswini Pedapati, Horst Samulowitz, Martin Wistuba, Yunyao Li:
AutoText: An End-to-End AutoAI Framework for Text. AAAI 2021: 16001-16003 - [c47]Hoang Thanh Lam, Beat Buesser, Hong Min, Tran Ngoc Minh, Martin Wistuba, Udayan Khurana, Gregory Bramble, Theodoros Salonidis, Dakuo Wang, Horst Samulowitz:
Automated Data Science for Relational Data. ICDE 2021: 2689-2692 - [c46]Syed Yousaf Shah, Dhaval Patel, Long Vu, Xuan-Hong Dang, Bei Chen, Peter Kirchner, Horst Samulowitz, David Wood, Gregory Bramble, Wesley M. Gifford, Giridhar Ganapavarapu, Roman Vaculín, Petros Zerfos:
AutoAI-TS: AutoAI for Time Series Forecasting. SIGMOD Conference 2021: 2584-2596 - [i15]Dakuo Wang, Q. Vera Liao, Yunfeng Zhang, Udayan Khurana, Horst Samulowitz, Soya Park, Michael J. Muller, Lisa Amini:
How Much Automation Does a Data Scientist Want? CoRR abs/2101.03970 (2021) - [i14]Syed Yousaf Shah, Dhaval Patel, Long Vu, Xuan-Hong Dang, Bei Chen, Peter Kirchner, Horst Samulowitz, David Wood, Gregory Bramble, Wesley M. Gifford, Giridhar Ganapavarapu, Roman Vaculín, Petros Zerfos:
AutoAI-TS: AutoAI for Time Series Forecasting. CoRR abs/2102.12347 (2021) - [i13]Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig:
FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning. CoRR abs/2112.08524 (2021) - 2020
- [c45]Sijia Liu, Parikshit Ram, Deepak Vijaykeerthy, Djallel Bouneffouf, Gregory Bramble, Horst Samulowitz, Dakuo Wang, Andrew Conn, Alexander G. Gray:
An ADMM Based Framework for AutoML Pipeline Configuration. AAAI 2020: 4892-4899 - [c44]Udayan Khurana, Horst Samulowitz:
Autonomous Predictive Modeling via Reinforcement Learning. CIKM 2020: 3285-3288 - [c43]Djallel Bouneffouf, Charu C. Aggarwal, Thanh Hoang, Udayan Khurana, Horst Samulowitz, Beat Buesser, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray:
Survey on Automated End-to-End Data Science? IJCNN 2020: 1-9 - [c42]Dakuo Wang, Parikshit Ram, Daniel Karl I. Weidele, Sijia Liu, Michael J. Muller, Justin D. Weisz, Abel N. Valente, Arunima Chaudhary, Dustin Ramsey Torres, Horst Samulowitz, Lisa Amini:
AutoAI: Automating the End-to-End AI Lifecycle with Humans-in-the-Loop. IUI Companion 2020: 77-78 - [c41]Dakuo Wang, Josh Andres, Justin D. Weisz, Erick Oduor, Udayan Khurana, Horst Samulowitz, Arunima Chaudhary, Abel N. Valente, Dustin Ramsey Torres, Casey Dugan:
IBM AutoAI: Human-in-the-Loop Automated Machine Learning Supports Data Scientists to Build Better Models. DaSH@KDD 2020 - [i12]Parikshit Ram, Sijia Liu, Deepak Vijaykeerthy, Dakuo Wang, Djallel Bouneffouf, Gregory Bramble, Horst Samulowitz, Alexander G. Gray:
Solving Constrained CASH Problems with ADMM. CoRR abs/2006.09635 (2020)
2010 – 2019
- 2019
- [j4]Dakuo Wang, Justin D. Weisz, Michael J. Muller, Parikshit Ram, Werner Geyer, Casey Dugan, Yla R. Tausczik, Horst Samulowitz, Alexander G. Gray:
Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI. Proc. ACM Hum. Comput. Interact. 3(CSCW): 211:1-211:24 (2019) - [c40]Silvan Sievers, Michael Katz, Shirin Sohrabi, Horst Samulowitz, Patrick Ferber:
Deep Learning for Cost-Optimal Planning: Task-Dependent Planner Selection. AAAI 2019: 7715-7723 - [c39]Sainyam Galhotra, Udayan Khurana, Oktie Hassanzadeh, Kavitha Srinivas, Horst Samulowitz, Miao Qi:
Automated Feature Enhancement for Predictive Modeling using External Knowledge. ICDM Workshops 2019: 1094-1097 - [c38]Djallel Bouneffouf, Srinivasan Parthasarathy, Horst Samulowitz, Martin Wistuba:
Optimal Exploitation of Clustering and History Information in Multi-armed Bandit. IJCAI 2019: 2016-2022 - [i11]Atin Sood, Benjamin Elder, Benjamin Herta, Chao Xue, Costas Bekas, A. Cristiano I. Malossi, Debashish Saha, Florian Scheidegger, Ganesh Venkataraman, Gegi Thomas, Giovanni Mariani, Hendrik Strobelt, Horst Samulowitz, Martin Wistuba, Matteo Manica, Mihir R. Choudhury, Rong Yan, Roxana Istrate, Ruchir Puri, Tejaswini Pedapati:
NeuNetS: An Automated Synthesis Engine for Neural Network Design. CoRR abs/1901.06261 (2019) - [i10]Udayan Khurana, Horst Samulowitz:
Automating Predictive Modeling Process using Reinforcement Learning. CoRR abs/1903.00743 (2019) - [i9]Sijia Liu, Parikshit Ram, Djallel Bouneffouf, Gregory Bramble, Andrew R. Conn, Horst Samulowitz, Alexander G. Gray:
Automated Machine Learning via ADMM. CoRR abs/1905.00424 (2019) - [i8]Djallel Bouneffouf, Srinivasan Parthasarathy, Horst Samulowitz, Martin Wistuba:
Optimal Exploitation of Clustering and History Information in Multi-Armed Bandit. CoRR abs/1906.03979 (2019) - [i7]Dakuo Wang, Justin D. Weisz, Michael J. Muller, Parikshit Ram, Werner Geyer, Casey Dugan, Yla R. Tausczik, Horst Samulowitz, Alexander G. Gray:
Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI. CoRR abs/1909.02309 (2019) - [i6]Charu C. Aggarwal, Djallel Bouneffouf, Horst Samulowitz, Beat Buesser, Thanh Hoang, Udayan Khurana, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray:
How can AI Automate End-to-End Data Science? CoRR abs/1910.14436 (2019) - 2018
- [c37]Udayan Khurana, Horst Samulowitz, Deepak S. Turaga:
Feature Engineering for Predictive Modeling Using Reinforcement Learning. AAAI 2018: 3407-3414 - [c36]Fatemeh Nargesian, Udayan Khurana, Tejaswini Pedapati, Horst Samulowitz, Deepak S. Turaga:
Dataset Evolver: An Interactive Feature Engineering Notebook. AAAI 2018: 8212-8213 - 2017
- [j3]Gonzalo I. Diaz, Achille Fokoue-Nkoutche, Giacomo Nannicini, Horst Samulowitz:
An effective algorithm for hyperparameter optimization of neural networks. IBM J. Res. Dev. 61(4-5): 9:1-9:11 (2017) - [c35]Fatemeh Nargesian, Horst Samulowitz, Udayan Khurana, Elias B. Khalil, Deepak S. Turaga:
Learning Feature Engineering for Classification. IJCAI 2017: 2529-2535 - [i5]Gonzalo I. Diaz, Achille Fokoue, Giacomo Nannicini, Horst Samulowitz:
An effective algorithm for hyperparameter optimization of neural networks. CoRR abs/1705.08520 (2017) - [i4]Udayan Khurana, Horst Samulowitz, Deepak S. Turaga:
Feature Engineering for Predictive Modeling using Reinforcement Learning. CoRR abs/1709.07150 (2017) - [i3]Tejas Dharamsi, Payel Das, Tejaswini Pedapati, Gregory Bramble, Vinod Muthusamy, Horst Samulowitz, Kush R. Varshney, Yuvaraj Rajamanickam, John Thomas, Justin Dauwels:
Neurology-as-a-Service for the Developing World. CoRR abs/1711.06195 (2017) - 2016
- [c34]Andrea Loreggia, Yuri Malitsky, Horst Samulowitz, Vijay A. Saraswat:
Deep Learning for Algorithm Portfolios. AAAI 2016: 1280-1286 - [c33]Ashish Sabharwal, Horst Samulowitz, Gerald Tesauro:
Selecting Near-Optimal Learners via Incremental Data Allocation. AAAI 2016: 2007-2015 - [c32]Udayan Khurana, Deepak S. Turaga, Horst Samulowitz, Srinivasan Parthasrathy:
Cognito: Automated Feature Engineering for Supervised Learning. ICDM Workshops 2016: 1304-1307 - [c31]Alhussein Fawzi, Horst Samulowitz, Deepak S. Turaga, Pascal Frossard:
Adaptive data augmentation for image classification. ICIP 2016: 3688-3692 - [c30]Alhussein Fawzi, Horst Samulowitz, Deepak S. Turaga, Pascal Frossard:
Image inpainting through neural networks hallucinations. IVMSP 2016: 1-5 - [i2]Ashish Sabharwal, Horst Samulowitz, Gerald Tesauro:
Selecting Near-Optimal Learners via Incremental Data Allocation. CoRR abs/1601.00024 (2016) - 2015
- [c29]Alain Biem, Maria Butrico, Mark Feblowitz, Tim Klinger, Yuri Malitsky, Kenney Ng, Adam Perer, Chandra Reddy, Anton Riabov, Horst Samulowitz, Daby M. Sow, Gerald Tesauro, Deepak S. Turaga:
Towards Cognitive Automation of Data Science. AAAI 2015: 4268-4269 - [c28]Carlos Ansótegui, Yuri Malitsky, Horst Samulowitz, Meinolf Sellmann, Kevin Tierney:
Model-Based Genetic Algorithms for Algorithm Configuration. IJCAI 2015: 733-739 - 2014
- [c27]Ashish Sabharwal, Horst Samulowitz:
Insights into Parallelism with Intensive Knowledge Sharing. CP 2014: 655-671 - [c26]David Bergman, André A. Ciré, Ashish Sabharwal, Horst Samulowitz, Vijay A. Saraswat, Willem Jan van Hoeve:
Parallel Combinatorial Optimization with Decision Diagrams. CPAIOR 2014: 351-367 - 2013
- [j2]Tom Schrijvers, Guido Tack, Pieter Wuille, Horst Samulowitz, Peter J. Stuckey:
Search combinators. Constraints An Int. J. 18(2): 269-305 (2013) - [c25]George Katsirelos, Ashish Sabharwal, Horst Samulowitz, Laurent Simon:
Resolution and Parallelizability: Barriers to the Efficient Parallelization of SAT Solvers. AAAI 2013: 481-488 - [c24]Ashish Sabharwal, Horst Samulowitz, Tom Schrijvers, Peter J. Stuckey, Guido Tack:
Automated Design of Search with Composability. AAAI (Late-Breaking Developments) 2013 - [c23]Tobias Achterberg, Ashish Sabharwal, Horst Samulowitz:
Stronger Inference through Implied Literals from Conflicts and Knapsack Covers. CPAIOR 2013: 1-11 - [c22]Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann:
Algorithm Portfolios Based on Cost-Sensitive Hierarchical Clustering. IJCAI 2013: 608-614 - [c21]Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann:
Boosting Sequential Solver Portfolios: Knowledge Sharing and Accuracy Prediction. LION 2013: 153-167 - [c20]Horst Samulowitz, Chandra Reddy, Ashish Sabharwal, Meinolf Sellmann:
Snappy: A Simple Algorithm Portfolio. SAT 2013: 422-428 - 2012
- [c19]Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann:
Parallel SAT Solver Selection and Scheduling. CP 2012: 512-526 - [c18]Ashish Sabharwal, Horst Samulowitz, Chandra Reddy:
Guiding Combinatorial Optimization with UCT. CPAIOR 2012: 356-361 - [c17]Tom Schrijvers, Guido Tack, Pieter Wuille, Horst Samulowitz, Peter J. Stuckey:
An Introduction to Search Combinators. LOPSTR 2012: 2-16 - [c16]Bard Bloom, David Grove, Benjamin Herta, Ashish Sabharwal, Horst Samulowitz, Vijay A. Saraswat:
SatX10: A Scalable Plug&Play Parallel SAT Framework - (Tool Presentation). SAT 2012: 463-468 - [c15]Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann:
Learning Back-Clauses in SAT - (Poster Presentation). SAT 2012: 498-499 - [c14]Arie Matsliah, Ashish Sabharwal, Horst Samulowitz:
Augmenting Clause Learning with Implied Literals - (Poster Presentation). SAT 2012: 500-501 - [i1]Tom Schrijvers, Guido Tack, Pieter Wuille, Horst Samulowitz, Peter J. Stuckey:
Search Combinators. CoRR abs/1203.1095 (2012) - 2011
- [c13]Serdar Kadioglu, Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann:
Algorithm Selection and Scheduling. CP 2011: 454-469 - [c12]Tom Schrijvers, Guido Tack, Pieter Wuille, Horst Samulowitz, Peter J. Stuckey:
Search Combinators. CP 2011: 774-788 - [c11]Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann:
Non-Model-Based Algorithm Portfolios for SAT. SAT 2011: 369-370 - [c10]Pieter Wuille, Tom Schrijvers, Horst Samulowitz, Guido Tack, Peter J. Stuckey:
Memoizing a Monadic Mixin DSL. WFLP 2011: 68-85 - 2010
- [c9]David H. Stern, Horst Samulowitz, Ralf Herbrich, Thore Graepel, Luca Pulina, Armando Tacchella:
Collaborative Expert Portfolio Management. AAAI 2010: 179-184
2000 – 2009
- 2009
- [c8]Lucas Bordeaux, Youssef Hamadi, Horst Samulowitz:
Experiments with Massively Parallel Constraint Solving. IJCAI 2009: 443-448 - 2008
- [b1]Horst Samulowitz:
Solving Quantified Boolean Formulas. University of Toronto, Canada, 2008 - 2007
- [c7]Horst Samulowitz, Roland Memisevic:
Learning to Solve QBF. AAAI 2007: 255-260 - [c6]Lucas Bordeaux, Horst Samulowitz:
On the stochastic constraint satisfaction framework. SAC 2007: 316-320 - [c5]Horst Samulowitz, Fahiem Bacchus:
Dynamically Partitioning for Solving QBF. SAT 2007: 215-229 - 2006
- [c4]Horst Samulowitz, Jessica Davies, Fahiem Bacchus:
Preprocessing QBF. CP 2006: 514-529 - [c3]Horst Samulowitz, Fahiem Bacchus:
Binary Clause Reasoning in QBF. SAT 2006: 353-367 - 2005
- [c2]Horst Samulowitz, Fahiem Bacchus:
Using SAT in QBF. CP 2005: 578-592 - 2001
- [j1]Walter Oberschelp, Alexander Hornung, Horst Samulowitz:
Visualization of eclipses and planetary conjunction events. The interplay between model coherence, scaling and animation. Vis. Comput. 17(5): 310-317 (2001) - 2000
- [c1]Walter Oberschelp, Alexander Hornung, Horst Samulowitz:
Visualization of Eclipses and Planetary Conjunction Events: The Interplay between Model Coherence, Scaling and Animation. Computer Graphics International 2000: 81-86
Coauthor Index
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