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- research-articleAugust 2024
TESLA: Thermally Safe, Load-Aware, and Energy-Efficient Cooling Control System for Data Centers
- Hanfei Geng,
- Yi Sun,
- Yuanzhe Li,
- Jichao Leng,
- Xiangyu Zhu,
- Xianyuan Zhan,
- Yuanchun Li,
- Feng Zhao,
- Yunxin Liu
ICPP '24: Proceedings of the 53rd International Conference on Parallel ProcessingAugust 2024, Pages 939–949https://doi.org/10.1145/3673038.3673144The increasing demand for artificial intelligence and cloud computing has led to skyrocketing energy consumption of data centers (DCs). This paper focuses on tackling this energy challenge through cooling control system optimization, which aims to ...
- tutorialFebruary 2024
Graph Time-series Modeling in Deep Learning: A Survey
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 5Article No.: 119, Pages 1–35https://doi.org/10.1145/3638534Time-series and graphs have been extensively studied for their ubiquitous existence in numerous domains. Both topics have been separately explored in the field of deep learning. For time-series modeling, recurrent neural networks or convolutional neural ...
- research-articleNovember 2021
Task-independent Recognition of Communication Skills in Group Interaction Using Time-series Modeling
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 17, Issue 4Article No.: 122, Pages 1–27https://doi.org/10.1145/3450283Case studies of group discussions are considered an effective way to assess communication skills (CS). This method can help researchers evaluate participants’ engagement with each other in a specific realistic context. In this article, multimodal analysis ...
- research-articleNovember 2010
On construction and simulation of autoregressive sources with near-laplace marginals
IEEE Transactions on Signal Processing (TSP), Volume 58, Issue 11November 2010, Pages 5550–5559https://doi.org/10.1109/TSP.2010.2062510In this paper, we focus upon the problem of modeling and simulation of stationary non-Gaussian time series. In particular, we consider a first order autoregressive process whose marginal distribution is close to the Laplace density. This model allows us ...
- ArticleSeptember 2009
Detecting Significant Events in Personal Image Collections
ICSC '09: Proceedings of the 2009 IEEE International Conference on Semantic ComputingSeptember 2009, Pages 116–123https://doi.org/10.1109/ICSC.2009.36The organization and retrieval of images and videos is a problem for the typical consumer. A typical image collection includes many pictures of common activities that are not considered to be important by the user. These images inflate the number of ...
- research-articleSeptember 2007
Monte Carlo Methods for Adaptive Sparse Approximations of Time-Series
IEEE Transactions on Signal Processing (TSP), Volume 55, Issue 9September 2007, Pages 4474–4486https://doi.org/10.1109/TSP.2007.896242This paper deals with adaptive sparse approximations of time-series. The work is based on a Bayesian specification of the shift-invariant sparse coding model. To learn approximations for a particular class of signals, two different learning strategies ...
- research-articleSeptember 1999
Parametric Hidden Markov Models for Gesture Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence (ITPM), Volume 21, Issue 9September 1999, Pages 884–900https://doi.org/10.1109/34.790429A new method for the representation, recognition, and interpretation of parameterized gesture is presented. By parameterized gesture we mean gestures that exhibit a systematic spatial variation; one example is a point gesture where the relevant ...