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2020 – today
- 2024
[j9]Michael Zhang, Samuel Kim, Peter Y. Lu, Marin Soljacic:
Deep Learning and Symbolic Regression for Discovering Parametric Equations. IEEE Trans. Neural Networks Learn. Syst. 35(11): 16775-16787 (2024)- [i16]Sunwoong Choi, Samuel Kim:
Data augmentation method for modeling health records with applications to clopidogrel treatment failure detection. CoRR abs/2402.18046 (2024) - [i15]Samuel Kim, Min-Sang Kim:
Leveraging Federated Learning for Automatic Detection of Clopidogrel Treatment Failures. CoRR abs/2403.03368 (2024) - [i14]Rishi Veerapaneni, Arthur Jakobsson, Kevin Ren, Samuel Kim, Jiaoyang Li, Maxim Likhachev:
Work Smarter Not Harder: Simple Imitation Learning with CS-PIBT Outperforms Large Scale Imitation Learning for MAPF. CoRR abs/2409.14491 (2024) - 2023
- [b1]Samuel Kim:
Novel Approaches to Discovery and Optimization in Physics: Symbolic Regression, Bayesian Optimization, and Topological Photonics. MIT, USA, 2023 - [j8]Garrett Parker
, Samuel Kim, Abdullah Al Maruf, Tomás Cerný, Karel Frajták, Pavel Tisnovsky, Davide Taibi:
Visualizing Anti-Patterns in Microservices at Runtime: A Systematic Mapping Study. IEEE Access 11: 4434-4442 (2023) - [c36]Soojin Lee, Ingu Sean Lee, Samuel Kim:
Predicting Development of Chronic Obstructive Pulmonary Disease and its Risk Factor Analysis. EMBC 2023: 1-4 - [c35]Won Joon Yun, Samuel Kim, Joongheon Kim:
Multi-Site Clinical Federated Learning Using Recursive and Attentive Models and NVFlare. ICDCS 2023: 1033-1036 - [i13]Willie Kang, Sean Kim, Eliot Yoo, Samuel Kim:
Predicting Students' Exam Scores Using Physiological Signals. CoRR abs/2301.12051 (2023) - [i12]Soojin Lee, Ingu Sean Lee, Samuel Kim:
Predicting Development of Chronic Obstructive Pulmonary Disease and its Risk Factor Analysis. CoRR abs/2302.03137 (2023) - [i11]Won Joon Yun, Samuel Kim, Joongheon Kim:
Multi-Site Clinical Federated Learning using Recursive and Attentive Models and NVFlare. CoRR abs/2306.16367 (2023) - [i10]Samuel Kim, Ingu Sean Lee, Mijeong Irene Ban, Jane Chiang:
Detection and prediction of clopidogrel treatment failures using longitudinal structured electronic health records. CoRR abs/2310.08757 (2023) - [i9]Sean Kim, Eliot Yoo, Samuel Kim:
Why Do Students Drop Out? University Dropout Prediction and Associated Factor Analysis Using Machine Learning Techniques. CoRR abs/2310.10987 (2023) - [i8]Sean Kim, Samuel Kim:
Automatic prediction of mortality in patients with mental illness using electronic health records. CoRR abs/2310.12121 (2023) - 2022
- [j7]Samuel Kim, Peter Y. Lu, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic:
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure. Trans. Mach. Learn. Res. 2022 (2022) - [c34]Dipta Das, Md Rofiqul Islam, Samuel Kim, Tomás Cerný, Karel Frajták, Miroslav Bures, Pavel Tisnovsky:
Analyzing Technical Debt by Mapping Production Logs with Source Code. SDSC 2022: 200-212 - [i7]Michael Zhang, Samuel Kim, Peter Y. Lu, Marin Soljacic:
Deep Learning and Symbolic Regression for Discovering Parametric Equations. CoRR abs/2207.00529 (2022) - 2021
- [j6]Samuel Kim, Peter Y. Lu, Srijon Mukherjee, Michael Gilbert, Li Jing, Vladimir Ceperic, Marin Soljacic:
Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery. IEEE Trans. Neural Networks Learn. Syst. 32(9): 4166-4177 (2021) - [c33]Young-Seong Cho, Samuel Kim, Jee-Hyong Lee:
Source Model Selection for Transfer Learning of Image Classification using Supervised Contrastive Loss. BigComp 2021: 325-329 - [c32]Namhee Kwon, Samuel Kim:
Depression Severity Detection Using Read Speech with a Divide-and-Conquer Approach. EMBC 2021: 633-637 - [c31]Min-Sub Won, YunSeok Choi, Samuel Kim, CheolWon Na, Jee-Hyong Lee:
An embedding method for unseen words considering contextual information and morphological information. SAC 2021: 1055-1062 - [i6]Samuel Kim, Peter Y. Lu, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic:
Scalable and Flexible Deep Bayesian Optimization with Auxiliary Information for Scientific Problems. CoRR abs/2104.11667 (2021) - [i5]Charlotte Loh, Thomas Christensen, Rumen Dangovski, Samuel Kim, Marin Soljacic:
Surrogate- and invariance-boosted contrastive learning for data-scarce applications in science. CoRR abs/2110.08406 (2021) - 2020
- [c30]Samuel Kim, Namhee Kwon, Henry O'Connell, Nathan Fisk, Scott Ferguson, Mark Bartlett:
"How are you?" Estimation of anxiety, sleep quality, and mood using computational voice analysis. EMBC 2020: 5369-5373 - [i4]Allan dos Santos Costa, Rumen Dangovski, Samuel Kim, Pawan Goyal, Marin Soljacic, Joseph Jacobson:
Interpretable Neuroevolutionary Models for Learning Non-Differentiable Functions and Programs. CoRR abs/2007.10784 (2020)
2010 – 2019
- 2019
- [i3]Peter Y. Lu, Samuel Kim, Marin Soljacic:
Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning. CoRR abs/1907.06011 (2019) - [i2]Samuel Kim, Namhee Kwon, Henry O'Connell:
Toward estimating personal well-being using voice. CoRR abs/1910.10082 (2019) - [i1]Samuel Kim, Peter Y. Lu, Srijon Mukherjee, Michael Gilbert, Li Jing, Vladimir Ceperic, Marin Soljacic:
Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery. CoRR abs/1912.04825 (2019) - 2018
- [c29]Samuel Kim, David Shrekenhamer, Jeffrey Will, Ra'id Awadallah, Joseph A. Miragliotta:
High impedance holographic metasurfaces for conformal and high gain antenna applications. CCNC 2018: 1-4 - [c28]Rohil Verma, Samuel Kim, David Walter:
Syntactical Analysis of the Weaknesses of Sentiment Analyzers. EMNLP 2018: 1122-1127 - 2014
- [j5]Samuel Kim, Fabio Valente, Maurizio Filippone, Alessandro Vinciarelli:
Predicting Continuous Conflict Perceptionwith Bayesian Gaussian Processes. IEEE Trans. Affect. Comput. 5(2): 187-200 (2014) - [c27]Jung-Won Lee, Samuel Kim, Hong-Goo Kang:
Detecting pathological speech using contour modeling of harmonic-to-noise ratio. ICASSP 2014: 5969-5973 - 2013
- [j4]Eric W. Hall, Samuel Kim, Visham Appadoo, Richard N. Zare:
Lysis of a Single Cyanobacterium for Whole Genome Amplification. Micromachines 4(3): 321-332 (2013) - [c26]Jung-Won Lee, Hong-Goo Kang, Samuel Kim, Yoonjae Lee:
Detecting pathological speech using local and global characteristics of harmonic-to-noise ratio. APSIPA 2013: 1-4 - [c25]Samuel Kim, Panayiotis G. Georgiou, Shrikanth S. Narayanan:
On-line genre classification of TV programs using audio content. ICASSP 2013: 798-802 - [c24]Björn W. Schuller, Stefan Steidl, Anton Batliner, Alessandro Vinciarelli, Klaus R. Scherer, Fabien Ringeval, Mohamed Chetouani, Felix Weninger, Florian Eyben, Erik Marchi, Marcello Mortillaro, Hugues Salamin, Anna Polychroniou, Fabio Valente, Samuel Kim:
The INTERSPEECH 2013 computational paralinguistics challenge: social signals, conflict, emotion, autism. INTERSPEECH 2013: 148-152 - [c23]Samuel Kim, Panayiotis G. Georgiou, Shrikanth S. Narayanan:
Annotation and classification of Political advertisements. INTERSPEECH 2013: 1092-1096 - [c22]Samuel Kim, Fabio Valente, Alessandro Vinciarelli:
Annotation and detection of conflict escalation in Political debates. INTERSPEECH 2013: 1409-1413 - 2012
- [c21]Samuel Kim, Panayiotis G. Georgiou, Shrikanth S. Narayanan:
Supervised acoustic topic model with a consequent classifier for unstructured audio classification. CBMI 2012: 1-6 - [c20]Samuel Kim, Fabio Valente, Alessandro Vinciarelli:
Automatic detection of conflicts in spoken conversations: Ratings and analysis of broadcast political debates. ICASSP 2012: 5089-5092 - [c19]Samuel Kim, Sree Harsha Yella, Fabio Valente:
Automatic detection of conflict escalation in spoken conversations. INTERSPEECH 2012: 1167-1170 - [c18]Fabio Valente, Samuel Kim, Petr Motlícek:
Annotation and Recognition of Personality Traits in Spoken Conversations from the AMI Meetings Corpus. INTERSPEECH 2012: 1183-1186 - [c17]Samuel Kim, Maurizio Filippone, Fabio Valente, Alessandro Vinciarelli:
Predicting the conflict level in television political debates: an approach based on crowdsourcing, nonverbal communication and gaussian processes. ACM Multimedia 2012: 793-796 - 2011
- [c16]Samuel Kim, Ming Li, Sangwon Lee, Urbashi Mitra, B. Adar Emken, Donna Spruijt-Metz, Murali Annavaram, Shrikanth S. Narayanan:
Modeling high-level descriptions of real-life physical activities using latent topic modeling of multimodal sensor signals. EMBC 2011: 6033-6036 - 2010
- [c15]Samuel Kim, Shiva Sundaram, Panayiotis G. Georgiou, Shrikanth S. Narayanan:
Acoustic stopwords for unstructured audio information retrieval. EUSIPCO 2010: 1277-1280 - [c14]Samuel Kim, Panayiotis G. Georgiou, Shrikanth S. Narayanan, Shiva Sundaram:
Using naïve text queries for robust audio information retrieval. ICASSP 2010: 2406-2409 - [c13]Daniel Bone, Samuel Kim, Sungbok Lee, Shrikanth S. Narayanan:
A study of intra-speaker and inter-speaker affective variability using electroglottograph and inverse filtered glottal waveforms. INTERSPEECH 2010: 913-916 - [c12]Samuel Kim, Shiva Sundaram, Panayiotis G. Georgiou, Shrikanth S. Narayanan:
An N-gram model for unstructured audio signals toward information retrieval. MMSP 2010: 477-480
2000 – 2009
- 2009
- [c11]Samuel Kim, Panayiotis G. Georgiou, Shrikanth S. Narayanan:
A robust harmony structure modeling scheme for classical music opus identification. ICASSP 2009: 1961-1964 - [c10]Samuel Kim, Shrikanth S. Narayanan, Shiva Sundaram:
Acoustic topic model for audio information retrieval. WASPAA 2009: 37-40 - 2008
- [j3]Carlos Busso, Murtaza Bulut, Chi-Chun Lee, Abe Kazemzadeh, Emily Mower, Samuel Kim, Jeannette N. Chang, Sungbok Lee, Shrikanth S. Narayanan:
IEMOCAP: interactive emotional dyadic motion capture database. Lang. Resour. Evaluation 42(4): 335-359 (2008) - [j2]Kyu Jeong Han, Samuel Kim, Shrikanth S. Narayanan:
Strategies to Improve the Robustness of Agglomerative Hierarchical Clustering Under Data Source Variation for Speaker Diarization. IEEE Trans. Speech Audio Process. 16(8): 1590-1601 (2008) - [c9]Samuel Kim, Erdem Unal, Shrikanth S. Narayanan:
Music fingerprint extraction for classical music cover song identification. ICME 2008: 1261-1264 - [c8]Samuel Kim, Shrikanth S. Narayanan:
Dynamic chroma feature vectors with applications to cover song identification. MMSP 2008: 984-987 - 2007
- [c7]Kyu Jeong Han, Samuel Kim, Shrikanth S. Narayanan:
Robust speaker clustering strategies to data source variation for improved speaker diarization. ASRU 2007: 262-267 - [c6]Samuel Kim, Panayiotis G. Georgiou, Sungbok Lee, Shrikanth S. Narayanan:
Real-time Emotion Detection System using Speech: Multi-modal Fusion of Different Timescale Features. MMSP 2007: 48-51 - 2005
- [j1]Thomas Eriksson, Samuel Kim, Hong-Goo Kang, Chungyong Lee:
An information-theoretic perspective on feature selection in speaker recognition. IEEE Signal Process. Lett. 12(7): 500-503 (2005) - [c5]Samuel Kim, Sung-Wan Yoon, Thomas Eriksson, Hong-Goo Kang, Dae Hee Youn:
A noise-robust pitch synchronous feature extraction algorithm for speaker recognition systems. INTERSPEECH 2005: 2029-2032 - 2004
- [c4]Samuel Kim, Thomas Eriksson, Hong-Goo Kang, Dae Hee Youn:
A pitch synchronous feature extraction method for speaker recognition. ICASSP (1) 2004: 405-408 - [c3]Thomas Eriksson, Samuel Kim, Hong-Goo Kang, Chungyong Lee:
Theory for speaker recognition over IP. INTERSPEECH 2004: 625-628 - [c2]Samuel Kim, Thomas Eriksson, Hong-Goo Kang:
On the time variability of vocal tract for speaker recognition. INTERSPEECH 2004: 2377-2380 - 2001
- [c1]Damianos Chatziantoniou, Michael O. Akinde, Theodore Johnson, Samuel Kim:
The MD-join: An Operator for Complex OLAP. ICDE 2001: 524-533
Coauthor Index
aka: Shrikanth S. Narayanan
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last updated on 2024-11-11 21:28 CET by the dblp team
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