Search Results for author: Daniel Lee

Found 20 papers, 3 papers with code

Increasing Coverage and Precision of Textual Information in Multilingual Knowledge Graphs

1 code implementation27 Nov 2023 Simone Conia, Min Li, Daniel Lee, Umar Farooq Minhas, Ihab Ilyas, Yunyao Li

Recent work in Natural Language Processing and Computer Vision has been using textual information -- e. g., entity names and descriptions -- available in knowledge graphs to ground neural models to high-quality structured data.

Entity Linking Machine Translation +1

From Pseudorandomness to Multi-Group Fairness and Back

no code implementations21 Jan 2023 Cynthia Dwork, Daniel Lee, Huijia Lin, Pranay Tankala

We identify and explore connections between the recent literature on multi-group fairness for prediction algorithms and the pseudorandomness notions of leakage-resilience and graph regularity.

Fairness LEMMA

AuraSense: Robot Collision Avoidance by Full Surface Proximity Detection

no code implementations10 Aug 2021 Xiaoran Fan, Riley Simmons-Edler, Daewon Lee, Larry Jackel, Richard Howard, Daniel Lee

In this paper, we introduce the phenomenon of the Leaky Surface Wave (LSW), a novel sensing modality, and present AuraSense, a proximity detection system using the LSW.

Collision Avoidance

Online Minimax Multiobjective Optimization: Multicalibeating and Other Applications

no code implementations9 Aug 2021 Daniel Lee, Georgy Noarov, Mallesh Pai, Aaron Roth

We introduce a simple but general online learning framework in which a learner plays against an adversary in a vector-valued game that changes every round.

Multiobjective Optimization

Answering Chinese Elementary School Social Study Multiple Choice Questions

no code implementations26 Jun 2021 Daniel Lee, Chao-Chun Liang, Keh-Yih Su

We present a novel approach to answer the Chinese elementary school Social Study Multiple Choice questions.

Multiple-choice Negation +1

Auxiliary Sequence Labeling Tasks for Disfluency Detection

no code implementations24 Oct 2020 Dongyub Lee, Byeongil Ko, Myeong Cheol Shin, Taesun Whang, Daniel Lee, Eun Hwa Kim, EungGyun Kim, Jaechoon Jo

Existing works for disfluency detection have focused on designing a single objective only for disfluency detection, while auxiliary objectives utilizing linguistic information of a word such as named entity or part-of-speech information can be effective.

named-entity-recognition Named Entity Recognition +4

Experiments in Extractive Summarization: Integer Linear Programming, Term/Sentence Scoring, and Title-driven Models

no code implementations1 Aug 2020 Daniel Lee, Rakesh Verma, Avisha Das, Arjun Mukherjee

In this paper, we revisit the challenging problem of unsupervised single-document summarization and study the following aspects: Integer linear programming (ILP) based algorithms, Parameterized normalization of term and sentence scores, and Title-driven approaches for summarization.

Document Summarization Extractive Summarization +1

Reference and Document Aware Semantic Evaluation Methods for Korean Language Summarization

no code implementations COLING 2020 Dongyub Lee, Myeongcheol Shin, Taesun Whang, Seungwoo Cho, Byeongil Ko, Daniel Lee, EungGyun Kim, Jaechoon Jo

In this paper, we propose evaluation metrics that reflect semantic meanings of a reference summary and the original document, Reference and Document Aware Semantic Score (RDASS).

Text Summarization

Robotic Grasping through Combined image-Based Grasp Proposal and 3D Reconstruction

no code implementations3 Mar 2020 Tarik Tosun, Daniel Yang, Ben Eisner, Volkan Isler, Daniel Lee

We present a novel approach to robotic grasp planning using both a learned grasp proposal network and a learned 3D shape reconstruction network.

Robotics

Cephalometric Landmark Detection by Attentive Feature Pyramid Fusion and Regression-Voting

no code implementations10 Oct 2019 Runnan Chen, Yuexin Ma, Nenglun Chen, Daniel Lee, and Wenping Wang

Marking anatomical landmarks in cephalometric radiography is a critical operation in cephalometric analysis.

regression

QXplore: Q-Learning Exploration by Maximizing Temporal Difference Error

no code implementations25 Sep 2019 Riley Simmons-Edler, Ben Eisner, Daniel Yang, Anthony Bisulco, Eric Mitchell, Sebastian Seung, Daniel Lee

We implement the objective with an adversarial Q-learning method in which Q and Qx are the action-value functions for extrinsic and secondary rewards, respectively.

Continuous Control Q-Learning +2

Cephalometric Landmark Detection by AttentiveFeature Pyramid Fusion and Regression-Voting

2 code implementations23 Aug 2019 Runnan Chen, Yuexin Ma, Nenglun Chen, Daniel Lee, Wenping Wang

Marking anatomical landmarks in cephalometric radiography is a critical operation in cephalometric analysis.

regression

Newswire versus Social Media for Disaster Response and Recovery

no code implementations25 Jun 2019 Rakesh Verma, Samaneh Karimi, Daniel Lee, Omprakash Gnawali, Azadeh Shakery

In a disaster situation, first responders need to quickly acquire situational awareness and prioritize response based on the need, resources available and impact.

Disaster Response

Reward Prediction Error as an Exploration Objective in Deep RL

no code implementations19 Jun 2019 Riley Simmons-Edler, Ben Eisner, Daniel Yang, Anthony Bisulco, Eric Mitchell, Sebastian Seung, Daniel Lee

We then propose a deep reinforcement learning method, QXplore, which exploits the temporal difference error of a Q-function to solve hard exploration tasks in high-dimensional MDPs.

Atari Games Continuous Control +4

Q-Learning for Continuous Actions with Cross-Entropy Guided Policies

no code implementations25 Mar 2019 Riley Simmons-Edler, Ben Eisner, Eric Mitchell, Sebastian Seung, Daniel Lee

CGP aims to combine the stability and performance of iterative sampling policies with the low computational cost of a policy network.

Q-Learning Reinforcement Learning (RL)

Identifying Reference Spans: Topic Modeling and Word Embeddings help IR

no code implementations9 Aug 2017 Luis Moraes, Shahryar Baki, Rakesh Verma, Daniel Lee

The CL-SciSumm 2016 shared task introduced an interesting problem: given a document D and a piece of text that cites D, how do we identify the text spans of D being referenced by the piece of text?

Topic Models Word Embeddings

Extractive Summarization: Limits, Compression, Generalized Model and Heuristics

no code implementations18 Apr 2017 Rakesh Verma, Daniel Lee

Due to its promise to alleviate information overload, text summarization has attracted the attention of many researchers.

Document Summarization Extractive Summarization +1

The Stan Math Library: Reverse-Mode Automatic Differentiation in C++

1 code implementation23 Sep 2015 Bob Carpenter, Matthew D. Hoffman, Marcus Brubaker, Daniel Lee, Peter Li, Michael Betancourt

As computational challenges in optimization and statistical inference grow ever harder, algorithms that utilize derivatives are becoming increasingly more important.

Mathematical Software G.1.0; G.1.3; G.1.4; F.2.1

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