Tune in on Tuesday, April 27th at 11:00 AM EST to hear our labmate, Josh Peeples, present in Boston University’s virtual ECE seminar! Josh will be presenting his current dissertation work on “Connecting the Past and Present: Histogram Layers for… Read More
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CONGRATULATIONS TO YIMING CUI FOR ACCEPTING AN INTERNSHIP AT BYTEDANCE RESEARCH LAB!
Congratulations to our labmate, Yiming Cui, for accepting an internship at ByteDance Research Lab! Yiming will be working on the data science team to develop computer vision, computer graphics and machine learning applications for ByteDance products (such as TikTok). Great… Read More
SPECTRAL VARIABILITY IN HSI ACCEPTED TO GRSM!
Congratulations to our labmates and collaborators: Ricardo Augusto Borsoi, Tales Imbiriba, Jose Carlos Moreira Bermudez, Cedric Richard, Jocelyn Chanussot, Lucas Drumets, Jean-Yves Tourneret, Alina Zare and Christian Jutten! Their publication, “Spectral Variability in Hyperspectral Data Unmixing: A Comprehensive Review” was… Read More
WELCOME NEW PHD STUDENT RITESH CHOWDHRY!
The Machine Learning and Sensing Lab is excited to welcome Ritesh Chowdhry as a new Ph.D. student! Ritesh will receive his MS degree in Electrical & Computer Engineering from the University of Florida in May 2021. In our lab, Ritesh… Read More
WALKER PRESENTS AT UF 2021 UNDERGRADUATE RESEARCH SYMPOSIUM!
Congratulations to our labmate, Sarah Walker! Sarah presented her work, titled “Divergence Regulated Encoder Network for Joint Dimensionality Reduction and Classification” at UF’s 2021 Undergraduate Research Virtual Symposium. The virtual symposium featured outstanding undergraduate researchers across all colleges at UF.… Read More
DIVERGENCE REGULATED ENCODER NETWORK FOR JOINT DIMENSIONALITY REDUCTION AND CLASSIFICATION
Abstract: In this paper, we investigate performing joint dimensionality reduction and classification using a novel histogram neural network. Motivated by a popular dimensionality reduction approach, t-Distributed Stochastic Neighbor Embedding (t-SNE), our proposed method incorporates a classification loss computed on samples… Read More
SUEN AWARDED NSF GRFP!
Congratulations to Gatorsense alumnus, Daniel Suen! Daniel was recently awarded a Graduate Research Fellowship by the National Science Foundation to fund his Ph.D. work in Statistics at the University of Washington. We are so proud of you, Daniel. Keep… Read More
DIVISIVE CLUSTERING ACCEPTED TO MLDM!
Congratulations to our labmates and collaborators: Diandra Prioleau, Kiana Alikhademi, Armisha Roberts, Joshua Peeples, Alina Zare and Juan Gilbert! Their paper, “Application of Divisive Clustering for Reducing Bias in Imbalanced Data” was recently accepted to the the 2021 International Conference… Read More
APPLICATION OF DIVISIVE CLUSTERING FOR REDUCING BIAS IN IMBALANCED DATA
Abstract: A lack of diversity and representativeness within training data causes bias in the machine learning pipeline by influencing the performance of many machine learning models to favor the majority of samples that are most similar. It is necessary to… Read More
CONGRATULATIONS TO DR. SHENG ZOU, OUR LAB’S LATEST PHD GRADUATE!
Congratulations to Dr. Sheng Zou for graduating with his Ph.D.! Sheng’s dissertation is titled “Classification with Multi-Imprecise Labels.” His research focused on developing classification approaches under the multiple instance learning framework. The goal of Sheng’s work was to model… Read More