b'Joohyung Lee'

research

∙ 07/15/2023

Intuitive Access to Smartphone Settings Using Relevance Model Trained by Contrastive Learning

The more new features that are being added to smartphones, the harder it...

0 Joonyoung Kim, et al. ∙

research

∙ 07/15/2023

Safe Formulas in the General Theory of Stable Models

Safe first-order formulas generalize the concept of a safe rule, which p...

0 Joohyung Lee, et al. ∙

research

∙ 07/15/2023

Elementary Sets for Logic Programs

By introducing the concepts of a loop and a loop formula, Lin and Zhao s...

0 Martin Gebser, et al. ∙

research

∙ 07/15/2023

First-Order Stable Model Semantics with Intensional Functions

In classical logic, nonBoolean fluents, such as the location of an objec...

0 Michael Bartholomew, et al. ∙

research

∙ 07/15/2023

NeurASP: Embracing Neural Networks into Answer Set Programming

We present NeurASP, a simple extension of answer set programs by embraci...

0 Zhun Yang, et al. ∙

research

∙ 07/15/2023

Leveraging Large Language Models to Generate Answer Set Programs

Large language models (LLMs), such as GPT-3 and GPT-4, have demonstrated...

0 Adam Ishay, et al. ∙

research

∙ 07/15/2023

Coupling Large Language Models with Logic Programming for Robust and General Reasoning from Text

While large language models (LLMs), such as GPT-3, appear to be robust a...

0 Zhun Yang, et al. ∙

research

∙ 07/10/2023

Learning to Solve Constraint Satisfaction Problems with Recurrent Transformer

Constraint satisfaction problems (CSPs) are about finding values of vari...

0 Zhun Yang, et al. ∙

research

∙ 07/10/2023

Injecting Logical Constraints into Neural Networks via Straight-Through Estimators

Injecting discrete logical constraints into neural network learning is o...

0 Zhun Yang, et al. ∙

research

∙ 05/04/2023

Learning Missing Modal Electronic Health Records with Unified Multi-modal Data Embedding and Modality-Aware Attention

Electronic Health Record (EHR) provides abundant information through var...

0 Kwanhyung Lee, et al. ∙

research

∙ 10/29/2022

Self-supervised predictive coding and multimodal fusion advance patient deterioration prediction in fine-grained time resolution

In the Emergency Department (ED), accurate prediction of critical events...

0 Kwanhyung Lee, et al. ∙

research

∙ 09/13/2022

Moving from 2D to 3D: volumetric medical image classification for rectal cancer staging

Volumetric images from Magnetic Resonance Imaging (MRI) provide invaluab...

0 Joohyung Lee, et al. ∙

research

∙ 03/27/2022

Bunched LPCNet2: Efficient Neural Vocoders Covering Devices from Cloud to Edge

Text-to-Speech (TTS) services that run on edge devices have many advanta...

0 Sangjun Park, et al. ∙

research

∙ 09/18/2019

Strong Equivalence for LPMLN Programs

LPMLN is a probabilistic extension of answer set programs with the weigh...

0 Joohyung Lee, et al. ∙

research

∙ 07/31/2019

Bridging Commonsense Reasoning and Probabilistic Planning via a Probabilistic Action Language

To be responsive to dynamically changing real-world environments, an int...

0 Yi Wang, et al. ∙

research

∙ 06/21/2019

Explainable Fact Checking with Probabilistic Answer Set Programming

One challenge in fact checking is the ability to improve the transparenc...

0 Naser Ahmadi, et al. ∙

research

∙ 04/01/2019

Elaboration Tolerant Representation of Markov Decision Process via Decision-Theoretic Extension of Probabilistic Action Language pBC+

We extend probabilistic action language pBC+ with the notion of utility ...

0 Yi Wang, et al. ∙

research

∙ 01/22/2019

Fully Convolutional Network-based Multi-Task Learning for Rectum and Rectal Cancer Segmentation

In this study, we present a fully automatic method to segment both rectu...

6 Joohyung Lee, et al. ∙

research

∙ 01/22/2019

Multi-Task Learning with a Fully Convolutional Network for Rectum and Rectal Cancer Segmentation

In a rectal cancer treatment planning, the location of rectum and rectal...

0 Joohyung Lee, et al. ∙

research

∙ 08/14/2018

Weight Learning in a Probabilistic Extension of Answer Set Programs

LPMLN is a probabilistic extension of answer set programs with the weigh...

0 Joohyung Lee, et al. ∙

research

∙ 05/02/2018

Translating LPOD and CR-Prolog2 into Standard Answer Set Programs

Logic Programs with Ordered Disjunction (LPOD) is an extension of standa...

0 Joohyung Lee, et al. ∙

research

∙ 05/02/2018

A Probabilistic Extension of Action Language BC+

We present a probabilistic extension of action language BC+. Just like B...

0 Joohyung Lee, et al. ∙

research

∙ 07/20/2017

Representing Hybrid Automata by Action Language Modulo Theories

Both hybrid automata and action languages are formalisms for describing ...

0 Joohyung Lee, et al. ∙

research

∙ 07/19/2017

Computing LPMLN Using ASP and MLN Solvers

LPMLN is a recent addition to probabilistic logic programming languages....

0 Joohyung Lee, et al. ∙

research

∙ 06/28/2016

On the Semantic Relationship between Probabilistic Soft Logic and Markov Logic

Markov Logic Networks (MLN) and Probabilistic Soft Logic (PSL) are widel...

0 Joohyung Lee, et al. ∙

research

∙ 01/18/2014

Reformulating the Situation Calculus and the Event Calculus in the General Theory of Stable Models and in Answer Set Programming

Circumscription and logic programs under the stable model semantics are ...

0 Joohyung Lee, et al. ∙

research

∙ 01/16/2014

First-Order Stable Model Semantics and First-Order Loop Formulas

Lin and Zhaos theorem on loop formulas states that in the propositional ...

0 Joohyung Lee, et al. ∙

research

∙ 12/20/2013

A Functional View of Strong Negation in Answer Set Programming

The distinction between strong negation and default negation has been us...

0 Michael Bartholomew, et al. ∙

research

∙ 01/08/2013

Two New Definitions of Stable Models of Logic Programs with Generalized Quantifiers

We present alternative definitions of the first-order stable model seman...

0 Joohyung Lee, et al. ∙

research

∙ 10/18/2012

Module Theorem for The General Theory of Stable Models

The module theorem by Janhunen et al. demonstrates how to provide a modu...

0 Joseph Babb, et al. ∙

research

∙ 03/23/2011

Representing First-Order Causal Theories by Logic Programs

Nonmonotonic causal logic, introduced by Norman McCain and Hudson Turner...

0 Paolo Ferraris, et al. ∙

research

∙ 12/28/2010

On Elementary Loops of Logic Programs

Using the notion of an elementary loop, Gebser and Schaub refined the th...

0 Martin Gebser, et al. ∙

Joohyung Lee

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