Prithviraj Sen | DeepAI

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∙ 07/05/2023

Learning Symbolic Rules over Abstract Meaning Representations for Textual Reinforcement Learning

Text-based reinforcement learning agents have predominantly been neural ...

0 Subhajit Chaudhury, et al. ∙

∙ 05/04/2023

Are Human Explanations Always Helpful? Towards Objective Evaluation of Human Natural Language Explanations

Human-annotated labels and explanations are critical for training explai...

0 Bingsheng Yao, et al. ∙

∙ 10/15/2022

A Closer Look at the Calibration of Differentially Private Learners

We systematically study the calibration of classifiers trained with diff...

0 Hanlin Zhang, et al. ∙

∙ 12/06/2021

Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks

Recent work on neuro-symbolic inductive logic programming has led to pro...

0 Prithviraj Sen, et al. ∙

∙ 09/16/2021

Combining Rules and Embeddings via Neuro-Symbolic AI for Knowledge Base Completion

Recent interest in Knowledge Base Completion (KBC) has led to a plethora...

36 Prithviraj Sen, et al. ∙

∙ 06/17/2021

LNN-EL: A Neuro-Symbolic Approach to Short-text Entity Linking

Entity linking (EL), the task of disambiguating mentions in text by link...

5 Hang Jiang, et al. ∙

∙ 04/08/2021

Deep Indexed Active Learning for Matching Heterogeneous Entity Representations

Given two large lists of records, the task in entity resolution (ER) is ...

0 Arjit Jain, et al. ∙

∙ 02/28/2021

Logic Embeddings for Complex Query Answering

Answering logical queries over incomplete knowledge bases is challenging...

0 Francois Luus, et al. ∙

∙ 10/01/2020

A Survey of the State of Explainable AI for Natural Language Processing

Recent years have seen important advances in the quality of state-of-the...

325 Marina Danilevsky, et al. ∙

∙ 04/06/2020

Forecasting in multivariate irregularly sampled time series with missing values

Sparse and irregularly sampled multivariate time series are common in cl...

0 Shivam Srivastava, et al. ∙

∙ 03/29/2020

A Comprehensive Benchmark Framework for Active Learning Methods in Entity Matching

Entity Matching (EM) is a core data cleaning task, aiming to identify di...

0 Venkata Vamsikrishna Meduri, et al. ∙

∙ 07/25/2019

HEIDL: Learning Linguistic Expressions with Deep Learning and Human-in-the-Loop

While the role of humans is increasingly recognized in machine learning ...

0 Yiwei Yang, et al. ∙

∙ 02/08/2018

Deep Learning with Apache SystemML

Enterprises operate large data lakes using Hadoop and Spark frameworks t...

0 Niketan Pansare, et al. ∙

∙ 01/02/2018

On Optimizing Operator Fusion Plans for Large-Scale Machine Learning in SystemML

Many large-scale machine learning (ML) systems allow specifying custom M...

0 Matthias Boehm, et al. ∙

∙ 05/09/2012

Bisimulation-based Approximate Lifted Inference

There has been a great deal of recent interest in methods for performing...

0 Prithviraj Sen, et al. ∙

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