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2020 – today
- 2025
[j7]Hadar Ben-Efraim
, Susan B. Davidson, Amit Somech:
SHARQ: Explainability Framework for Association Rules on Relational Data. Proc. ACM Manag. Data 3(1): 76:1-76:25 (2025)- [c21]Tavor Lipman, Tova Milo, Amit Somech, Tomer Wolfson, Oz Zafar:
LINX: A Language Driven Generative System for Goal-Oriented Automated Data Exploration. EDBT 2025: 270-283 - 2024
- [j6]Itay Elyashiv, Amir Gilad, Edna Isakov, Tal Tikochinsky, Amit Somech:
PD-Explain: A Unified Python-native Framework for Query Explanations Over DataFrames. Proc. VLDB Endow. 17(12): 4473-4476 (2024) - [i7]Tavor Lipman, Tova Milo, Amit Somech, Tomer Wolfson, Oz Zafar:
LINX: A Language Driven Generative System for Goal-Oriented Automated Data Exploration. CoRR abs/2406.05107 (2024) - [i6]Yevgeni Berkovitch, Oren Glickman, Amit Somech, Tomer Wolfson:
Generating Tables from the Parametric Knowledge of Language Models. CoRR abs/2406.10922 (2024) - [i5]Hadar Ben-Efraim, Susan B. Davidson, Amit Somech:
SHARQ: Explainability Framework for Association Rules on Relational Data. CoRR abs/2412.18522 (2024) - [i4]Sariel Ofek, Amit Somech:
Explaining Black-Box Clustering Pipelines With Cluster-Explorer. CoRR abs/2412.20446 (2024) - 2023
- [c20]Ido Ikar, Amit Somech:
EFFECTS: Explorable and Explainable Feature Extraction Framework for Multivariate Time-Series Classification. CIKM 2023: 5061-5065 - [c19]Sariel Tutay, Amit Somech:
Cluster-Explorer: An interactive Framework for Explaining Black-Box Clustering Results. CIKM 2023: 5106-5110 - [c18]Yael Amsterdamer, Susan B. Davidson, Tova Milo, Kathy Razmadze, Amit Somech:
Selecting Sub-tables for Data Exploration. ICDE 2023: 2496-2509 - [c17]Tavor Lipman, Tova Milo, Amit Somech:
ATENA-PRO: Generating Personalized Exploration Notebooks with Constrained Reinforcement Learning. SIGMOD Conference Companion 2023: 167-170 - 2022
- [j5]Daniel Deutch, Amir Gilad, Tova Milo, Amit Mualem, Amit Somech:
FEDEX: An Explainability Framework for Data Exploration Steps. Proc. VLDB Endow. 15(13): 3854-3868 (2022) - [j4]Teddy Lazebnik, Amit Somech, Abraham Itzhak Weinberg:
SubStrat: A Subset-Based Optimization Strategy for Faster AutoML. Proc. VLDB Endow. 16(4): 772-780 (2022) - [c16]Teddy Lazebnik, Amit Somech:
Demonstrating SubStrat: A Subset-Based Strategy for Faster AutoML on Large Datasets. CIKM 2022: 4907-4911 - [c15]Kathy Razmadze, Yael Amsterdamer, Amit Somech, Susan B. Davidson, Tova Milo:
SubTab: Data Exploration with Informative Sub-Tables. SIGMOD Conference 2022: 2369-2372 - [i3]Kathy Razmadze, Yael Amsterdamer, Amit Somech, Susan B. Davidson, Tova Milo:
Selecting Sub-tables for Data Exploration. CoRR abs/2203.02754 (2022) - [i2]Teddy Lazebnik, Amit Somech, Abraham Itzhak Weinberg:
SubStrat: A Subset-Based Strategy for Faster AutoML. CoRR abs/2206.03070 (2022) - [i1]Daniel Deutch, Amir Gilad, Tova Milo, Amit Mualem, Amit Somech:
FEDEX: An Explainability Framework for Data Exploration Steps. CoRR abs/2209.06260 (2022) - 2020
- [b1]Amit Somech:
A Context-Sensitive Framework for Data Analysis. Tel Aviv University, Israel, 2020 - [j3]Daniel Deutch, Amir Gilad, Tova Milo, Amit Somech:
ExplainED: Explanations for EDA Notebooks. Proc. VLDB Endow. 13(12): 2917-2920 (2020) - [c14]Ori Bar El, Tova Milo, Amit Somech:
Towards Autonomous, Hands-Free Data Exploration. CIDR 2020 - [c13]Amit Somech, Tova Milo, Oded Elbaz:
Incremental Based Framework for Efficient Top-K Similarity Search in Interactive Data Analysis Sessions. EDBT 2020: 97-108 - [c12]Ori Bar El, Tova Milo, Amit Somech:
Automatically Generating Data Exploration Sessions Using Deep Reinforcement Learning. SIGMOD Conference 2020: 1527-1537 - [c11]Tova Milo, Amit Somech:
Automating Exploratory Data Analysis via Machine Learning: An Overview. SIGMOD Conference 2020: 2617-2622
2010 – 2019
- 2019
- [c10]Yael Amsterdamer, Tova Milo, Amit Somech, Brit Youngmann:
Declarative User Selection with Soft Constraints. CIKM 2019: 931-940 - [c9]Ori Bar El, Tova Milo, Amit Somech:
ATENA: An Autonomous System for Data Exploration Based on Deep Reinforcement Learning. CIKM 2019: 2873-2876 - [c8]Brit Youngmann, Tova Milo, Amit Somech:
Boosting SimRank with Semantics. EDBT 2019: 37-48 - [c7]Amit Somech, Tova Milo, Chai Ozeri:
Predicting "What is Interesting" by Mining Interactive-Data-Analysis Session Logs. EDBT 2019: 456-467 - [c6]Tova Milo, Amit Somech, Brit Youngmann:
SimMeme: A Search Engine for Internet Memes. ICDE 2019: 974-985 - 2018
- [c5]Tova Milo, Amit Somech:
Next-Step Suggestions for Modern Interactive Data Analysis Platforms. KDD 2018: 576-585 - [c4]Tova Milo, Amit Somech:
Deep Reinforcement-Learning Framework for Exploratory Data Analysis. aiDM@SIGMOD 2018: 4:1-4:4 - 2016
- [j2]Yael Amsterdamer, Tova Milo, Amit Somech, Brit Youngmann:
December: A Declarative Tool for Crowd Member Selection. Proc. VLDB Endow. 9(13): 1485-1488 (2016) - [c3]Tova Milo, Amit Somech:
REACT: Context-Sensitive Recommendations for Data Analysis. SIGMOD Conference 2016: 2137-2140 - 2015
- [c2]Yael Amsterdamer, Susan B. Davidson, Anna Kukliansky, Tova Milo, Slava Novgorodov, Amit Somech:
Managing General and Individual Knowledge in Crowd Mining Applications. CIDR 2015 - 2014
- [j1]Yael Amsterdamer, Susan B. Davidson, Tova Milo, Slava Novgorodov, Amit Somech:
Ontology Assisted Crowd Mining. Proc. VLDB Endow. 7(13): 1597-1600 (2014) - [c1]Yael Amsterdamer, Susan B. Davidson, Tova Milo, Slava Novgorodov, Amit Somech:
OASSIS: query driven crowd mining. SIGMOD Conference 2014: 589-600
Coauthor Index
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last updated on 2025-04-09 22:21 CEST by the dblp team
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