Efficient Large-Scale Visual Representation Learning And Evaluation

no code implementations • 22 May 2023 • Eden Dolev, Alaa Awad, Denisa Roberts, Zahra Ebrahimzadeh, Marcin Mejran, Vaibhav Malpani, Mahir Yavuz

Efficiently learning visual representations of items is vital for large-scale recommendations.

Recommendation Systems Representation Learning

adSformers: Personalization from Short-Term Sequences and Diversity of Representations in Etsy Ads

no code implementations • 2 Feb 2023 • Alaa Awad, Denisa Roberts, Eden Dolev, Andrea Heyman, Zahra Ebrahimzadeh, Zoe Weil, Marcin Mejran, Vaibhav Malpani, Mahir Yavuz

To this end we introduce a three-component module called the adSformer diversifiable personalization module (ADPM) that learns a dynamic user representation.

Deep Learning for Multi-Scale Changepoint Detection in Multivariate Time Series

no code implementations • 16 May 2019 • Zahra Ebrahimzadeh, Min Zheng, Selcuk Karakas, Samantha Kleinberg

Many real-world time series, such as in health, have changepoints where the system's structure or parameters change.

Time Series Time Series Analysis

Pyramid Recurrent Neural Networks for Multi-Scale Change-Point Detection

no code implementations • ICLR 2019 • Zahra Ebrahimzadeh, Min Zheng, Selcuk Karakas, Samantha Kleinberg

To address this, we show how changepoint detection can be treated as a supervised learning problem, and propose a new deep neural network architecture that can efficiently identify both abrupt and gradual changes at multiple scales.

Activity Recognition Change Point Detection +2