Search Results for author: H. V. Jagadish

Found 10 papers, 3 papers with code

ARM-Net: Adaptive Relation Modeling Network for Structured Data

1 code implementation5 Jul 2021 Shaofeng Cai, Kaiping Zheng, Gang Chen, H. V. Jagadish, Beng Chin Ooi, Meihui Zhang

The key idea is to model feature interactions with cross features selectively and dynamically, by first transforming the input features into exponential space, and then determining the interaction order and interaction weights adaptively for each cross feature.

Decision Making

Duoquest: A Dual-Specification System for Expressive SQL Queries

1 code implementation16 Mar 2020 Christopher Baik, Zhongjun Jin, Michael Cafarella, H. V. Jagadish

We present results from user studies in which Duoquest demonstrates a 62. 5% absolute increase in query construction accuracy over a state-of-the-art NLI and comparable accuracy to a PBE system on a more limited workload supported by the PBE system.

Databases

Responsible Scoring Mechanisms Through Function Sampling

no code implementations22 Nov 2019 Abolfazl Asudeh, H. V. Jagadish

We provide unbiased samplers for the entire function space, as well as a $\theta$-vicinity around a given function.

Database Meets Deep Learning: Challenges and Opportunities

no code implementations21 Jun 2019 Wei Wang, Meihui Zhang, Gang Chen, H. V. Jagadish, Beng Chin Ooi, Kian-Lee Tan

Deep learning has recently become very popular on account of its incredible success in many complex data-driven applications, such as image classification and speech recognition.

Image Classification Speech Recognition

PANDA: Facilitating Usable AI Development

no code implementations26 Apr 2018 Jinyang Gao, Wei Wang, Meihui Zhang, Gang Chen, H. V. Jagadish, Guoliang Li, Teck Khim Ng, Beng Chin Ooi, Sheng Wang, Jingren Zhou

In many complex applications such as healthcare, subject matter experts (e. g. Clinicians) are the ones who appreciate the importance of features that affect health, and their knowledge together with existing knowledge bases are critical to the end results.

Autonomous Driving

A Generic Inverted Index Framework for Similarity Search on the GPU - Technical Report

1 code implementation28 Mar 2016 Jingbo Zhou, Qi Guo, H. V. Jagadish, Luboš Krčál, Siyuan Liu, Wenhao Luan, Anthony K. H. Tung, Yueji Yang, Yuxin Zheng

We propose a novel generic inverted index framework on the GPU (called GENIE), aiming to reduce the programming complexity of the GPU for parallel similarity search of different data types.

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