Recently added

Towards Understanding Generalization via Analytical Learning Theory

Kawaguchi, Kenji; Benigo, Yoshua; Verma, Vikas; Kaelbling, Leslie Pack (2018-10-01)

This paper introduces a novel measure-theoretic theory for machine learning that does not require statistical assumptions. Based on this theory, a new regularization method in deep learning is derived and shown to ...

Using Dynamic Monitoring to Synthesize Models of Applications That Access Databases

Shen, Jiasi; Rinard, MArtin (2018-09-27)

We previously developed Konure, a tool that uses active learning to infer the functionality of database applications. An alternative approach is to observe the inputs, outputs, and database traffic from a running ...

Using Active Learning to Synthesize Models of Applications That Access Databases

Shen, Jiasi; Rinard, Martin (2018-08-28)

We present a new technique that uses active learning to infer models of applications that manipulate relational databases. This technique comprises a domain-specific language for modeling applications that access ...

DSpace@MIT

CSAIL Digital Archive: Recent submissions

Towards Understanding Generalization via Analytical Learning Theory

Using Dynamic Monitoring to Synthesize Models of Applications That Access Databases

Using Active Learning to Synthesize Models of Applications That Access Databases

CSAIL Digital Archive: Recent submissions

Towards Understanding Generalization via Analytical Learning Theory ﻿

Using Dynamic Monitoring to Synthesize Models of Applications That Access Databases ﻿

Using Active Learning to Synthesize Models of Applications That Access Databases ﻿

Towards Understanding Generalization via Analytical Learning Theory

Using Dynamic Monitoring to Synthesize Models of Applications That Access Databases

Using Active Learning to Synthesize Models of Applications That Access Databases