Search Results for author: Joohyung Lee

Found 19 papers, 1 papers with code

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

no code implementations13 Sep 2022 Joohyung Lee, Jieun Oh, Inkyu Shin, You-sung Kim, Dae Kyung Sohn, Tae-sung Kim, In So Kweon

In this study, we present a volumetric convolutional neural network to accurately discriminate T2 from T3 stage rectal cancer with rectal MR volumes.

Image Classification Medical Image Classification

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

no code implementations27 Mar 2022 Sangjun Park, Kihyun Choo, Joohyung Lee, Anton V. Porov, Konstantin Osipov, June Sig Sung

Text-to-Speech (TTS) services that run on edge devices have many advantages compared to cloud TTS, e. g., latency and privacy issues.

Dual Attention in Time and Frequency Domain for Voice Activity Detection

1 code implementation27 Mar 2020 Joohyung Lee, Youngmoon Jung, Hoirin Kim

The results show that the focal loss can improve the performance in various imbalance situations compared to the cross entropy loss, a commonly used loss function in VAD.

Action Detection Activity Detection

Strong Equivalence for LPMLN Programs

no code implementations18 Sep 2019 Joohyung Lee, Man Luo

We show that the verification of strong equivalence in LPMLN can be reduced to equivalence checking in classical logic via a reduct and choice rules as well as to equivalence checking under the "soft" logic of here-and-there.

Bridging Commonsense Reasoning and Probabilistic Planning via a Probabilistic Action Language

no code implementations31 Jul 2019 Yi Wang, Shiqi Zhang, Joohyung Lee

In this paper, we present a unified framework to integrate icorpp's reasoning and planning components.

Decision Making

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

no code implementations1 Apr 2019 Yi Wang, Joohyung Lee

Alternatively, the semantics of pBC+ can also be defined in terms of Markov Decision Process (MDP), which in turn allows for representing MDP in a succinct and elaboration tolerant way as well as to leverage an MDP solver to compute pBC+.

Reducing the Model Variance of a Rectal Cancer Segmentation Network

no code implementations22 Jan 2019 Joohyung Lee, Ji Eun Oh, Min Ju Kim, Bo Yun Hur, Dae Kyung Sohn

As a result, adding a rectum segmentation task reduced the model variance of the rectal cancer segmentation network within tumor regions by a factor of 0. 90; data augmentation further reduced the variance by a factor of 0. 89.

Data Augmentation Image Segmentation +3

Weight Learning in a Probabilistic Extension of Answer Set Programs

no code implementations14 Aug 2018 Joohyung Lee, Yi Wang

Learning in LPMLN is in accordance with the stable model semantics, thereby it learns parameters for probabilistic extensions of knowledge-rich domains where answer set programming has shown to be useful but limited to the deterministic case, such as reachability analysis and reasoning about actions in dynamic domains.

Translating LPOD and CR-Prolog2 into Standard Answer Set Programs

no code implementations2 May 2018 Joohyung Lee, Zhun Yang

Logic Programs with Ordered Disjunction (LPOD) is an extension of standard answer set programs to handle preference using the construct of ordered disjunction, and CR-Prolog2 is an extension of standard answer set programs with consistency restoring rules and LPOD-like ordered disjunction.

A Probabilistic Extension of Action Language BC+

no code implementations2 May 2018 Joohyung Lee, Yi Wang

We present a probabilistic extension of action language BC+.

Representing Hybrid Automata by Action Language Modulo Theories

no code implementations20 Jul 2017 Joohyung Lee, Nikhil Loney, Yunsong Meng

We first show how to represent linear hybrid automata with convex invariants by an action language modulo theories.


Computing LPMLN Using ASP and MLN Solvers

no code implementations19 Jul 2017 Joohyung Lee, Samidh Talsania, Yi Wang

LPMLN is a recent addition to probabilistic logic programming languages.

On the Semantic Relationship between Probabilistic Soft Logic and Markov Logic

no code implementations28 Jun 2016 Joohyung Lee, Yi Wang

Markov Logic Networks (MLN) and Probabilistic Soft Logic (PSL) are widely applied formalisms in Statistical Relational Learning, an emerging area in Artificial Intelligence that is concerned with combining logical and statistical AI.

Relational Reasoning

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

no code implementations18 Jan 2014 Joohyung Lee, Ravi Palla

Based on the discovery that circumscription and the stable model semantics coincide on a class of canonical formulas, we reformulate the situation calculus and the event calculus in the general theory of stable models.


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

no code implementations16 Jan 2014 Joohyung Lee, Yunsong Meng

Lin and Zhaos theorem on loop formulas states that in the propositional case the stable model semantics of a logic program can be completely characterized by propositional loop formulas, but this result does not fully carry over to the first-order case.

A Functional View of Strong Negation in Answer Set Programming

no code implementations20 Dec 2013 Michael Bartholomew, Joohyung Lee

The distinction between strong negation and default negation has been useful in answer set programming.

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