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Short term forecast of wind power generation based on SVM with pattern matching (2016)
Presentation / Conference Contribution
Zhu, Z., Zhou, D., & Fan, Z. (2016, April). Short term forecast of wind power generation based on SVM with pattern matching. Paper presented at 2016 IEEE INTERNATIONAL ENERGY CONFERENCE (ENERGYCON), Leuven, Belgium

This paper investigates short term forecast of wind power generation using Support Vector Machine (SVM) methods. We propose a similar pattern matching technique for data pre-processing. The proposed technique is able to select the most appropriate se... Read More about Short term forecast of wind power generation based on SVM with pattern matching.

From Uruk to Ur: Automated Matching of Virtual Tablet Fragments (2016)
Presentation / Conference Contribution
Gehlken, E., Collins, T., Woolley, S., Hanes, L., Lewis, A., Hernandez Munoz, L., & Ch’ng, E. (2016, July). From Uruk to Ur: Automated Matching of Virtual Tablet Fragments. Paper presented at 62nd Rencontre Assyriologique Internationale 2016, Ur in the Twenty-First Century CE, Philadelphia

Observations of meteotsunami on the Louisiana shelf: a lone soliton with a soliton pack (2016)
Journal Article
Sheremet, A., Gravois, U., & Shrira, V. (2016). Observations of meteotsunami on the Louisiana shelf: a lone soliton with a soliton pack. Natural Hazards, 84, 471-492. https://doi.org/10.1007/s11069-016-2446-2

The paper reports unique high-resolution observations of meteotsunami by a large array of oceanographic instruments deployed on the Atchafalaya Shelf (Louisiana, USA) in 2008 with the primary aim to study wave dissipation in muddy environments. The m... Read More about Observations of meteotsunami on the Louisiana shelf: a lone soliton with a soliton pack.

Neuroevolution of Feedback Control for Object Manipulation by 3D Agents (2016)
Book Chapter
Stanton, A., & Channon, A. (2016). Neuroevolution of Feedback Control for Object Manipulation by 3D Agents. In Proceedings of the Artificial Life Conference 2016 (144-151)

Carlos Gershenson, Tom Froese, Jesus M. Siqueiros, Wendy Aguilar, Eduardo J. Izquierdo and Hiroki Sayama

Nonlinearity and Endogeneity in Continuous-Time Regime-Switching Diffusion Models for Market Volatility (2016)
Journal Article
Bu, R., Cheng, J., & Hadri, K. (2016). Nonlinearity and Endogeneity in Continuous-Time Regime-Switching Diffusion Models for Market Volatility. Studies in Nonlinear Dynamics and Econometrics, 21(1), https://doi.org/10.1515/snde-2016-0047

We examine model specification in regime-switching continuous-time diffusions for modeling S&P 500 Volatility Index (VIX). Our investigation is carried out under two nonlinear diffusion frameworks, the NLDCEV and the CIRCEV frameworks, and our focus... Read More about Nonlinearity and Endogeneity in Continuous-Time Regime-Switching Diffusion Models for Market Volatility.

Multimodal Multi-Stream Deep Learning for Egocentric Activity Recognition (2016)
Presentation / Conference Contribution
Song, S., Chandrasekhar, V., Mandal, B., Li, L., Lim, J.-H., Babu, G. S., San, P. P., & Cheung, N.-M. (2016, June). Multimodal Multi-Stream Deep Learning for Egocentric Activity Recognition. Presented at 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Las Vegas, NV, USA

In this paper, we propose a multimodal multi-stream deep learning framework to tackle the egocentric activity recognition problem, using both the video and sensor data. First, we experiment and extend a multi-stream Convolutional Neural Network to le... Read More about Multimodal Multi-Stream Deep Learning for Egocentric Activity Recognition.