Search Results for author:
Found 10 papers, 3 papers with code
Auto-Formula: Recommend Formulas in Spreadsheets using Contrastive Learning for Table Representations
Spreadsheets are widely recognized as the most popular end-user programming tools, which blend the power of formula-based computation, with an intuitive table-based interface.
Table-GPT: Table-tuned GPT for Diverse Table Tasks
Language models, such as GPT-3. 5 and ChatGPT, demonstrate remarkable abilities to follow diverse human instructions and perform a wide range of tasks.
Auto-Tables: Synthesizing Multi-Step Transformations to Relationalize Tables without Using Examples
Relational tables, where each row corresponds to an entity and each column corresponds to an attribute, have been the standard for tables in relational databases.
Auto-Validate by-History: Auto-Program Data Quality Constraints to Validate Recurring Data Pipelines
Data pipelines are widely employed in modern enterprises to power a variety of Machine-Learning (ML) and Business-Intelligence (BI) applications.
Auto-Tag: Tagging-Data-By-Example in Data Lakes
As data lakes become increasingly popular in large enterprises today, there is a growing need to tag or classify data assets (e. g., files and databases) in data lakes with additional metadata (e. g., semantic column-types), as the inferred metadata can enable a range of downstream applications like data governance (e. g., GDPR compliance), and dataset search.
Auto-Pipeline: Synthesizing Complex Data Pipelines By-Target Using Reinforcement Learning and Search
We in this work propose to automate multiple such steps end-to-end, by synthesizing complex data pipelines with both string transformations and table-manipulation operators.
TableQnA: Answering List Intent Queries With Web Tables
For (ii), we develop novel features to compute structure-aware match and train a machine learning model.
Petabytes to Science
A Kavli foundation sponsored workshop on the theme \emph{Petabytes to Science} was held 12$^{th}$ to 14$^{th}$ of February 2019 in Las Vegas.
Instrumentation and Methods for Astrophysics
Selectivity Estimation for Range Predicates using Lightweight Models
Query optimizers depend on selectivity estimates of query predicates to produce a good execution plan.
ABC: Efficient Selection of Machine Learning Configuration on Large Dataset
A machine learning configuration refers to a combination of preprocessor, learner, and hyperparameters.
