Randy Ardywibowo
Randy Ardywibowo
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BayesCNS: A Unified Bayesian Approach to Address Cold Start and Non-Stationarity in Search Systems at Scale
Information Retrieval (IR) systems used in search and recommendation platforms frequently employ Learning-to-Rank (LTR) models to rank …
Randy Ardywibowo
,
Rakesh Sunki
,
Lucy Kuo
,
Sankalp Nayak
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VariGrow: Variational Architecture Growing for Task-Agnostic Continual Learning based on Bayesian Novelty
Continual Learning (CL) is the problem of sequentially learning a set of tasks and preserving all the knowledge acquired. Many existing …
Randy Ardywibowo
,
Zepeng Huo
,
Zhangyang Wang
,
Bobak Mortazavi
,
Shuai Huang
,
Xiaoning Qian
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VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks
In many machine learning tasks, input features with varying degrees of predictive capability are acquired at varying costs. In order to …
Randy Ardywibowo
,
Shahin Boluki
,
Zhangyang Wang
,
Bobak Mortazavi
,
Shuai Huang
,
Xiaoning Qian
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NADS: Neural Architecture Distribution Search for Uncertainty Awareness
Machine learning (ML) systems often encounter Out-of-Distribution (OoD) errors when dealing with testing data coming from a …
Randy Ardywibowo
,
Shahin Boluki
,
Xinyu Gong
,
Zhangyang Wang
,
Xiaoning Qian
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Learnable Bernoulli Dropout for Bayesian Deep Learning
In this work, we propose learnable Bernoulli dropout (LBD), a new model-agnostic dropout scheme that considers the dropout rates as …
Shahin Boluki
,
Randy Ardywibowo
,
Siamak Zamani Dadaneh
,
Mingyuan Zhou
,
Xiaoning Qian
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Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models
Emerging wearable sensors have enabled the unprecedented ability to continuously monitor human activities for healthcare purposes. …
Randy Ardywibowo
,
Guang Zhao
,
Zhangyang Wang
,
Bobak Mortazavi
,
Shuai Huang
,
Xiaoning Qian
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