no code implementations • 4 May 2022 • Ravi Kumar, Shahin Boluki, Karl Isler, Jonas Rauch, Darius Walczak
To address this concern, we propose a two-stage estimation methodology which makes the estimation of the price-sensitivity parameters robust to biases in the estimators of the nuisance parameters of the model.
no code implementations • 31 Mar 2022 • Randy Ardywibowo, Shahin Boluki, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian
At its core is an implicit variational distribution on binary gates that are dependent on previous observations, which will select the next subset of features to observe.
1 code implementation • 4 Apr 2021 • Seyednami Niyakan, Ehsan Hajiramezanali, Shahin Boluki, Siamak Zamani Dadaneh, Xiaoning Qian
We develop a new method -- SimCD -- that explicitly models cell heterogeneity and dynamic differential changes in one unified hierarchical gamma-negative binomial (hGNB) model, allowing simultaneous cell clustering and differential expression analysis for scRNA-seq data.
no code implementations • 1 Jan 2021 • Randy Ardywibowo, Shahin Boluki, Zhangyang Wang, Bobak J Mortazavi, Shuai Huang, Xiaoning Qian
In many machine learning tasks, input features with varying degrees of predictive capability are usually acquired at some cost.
no code implementations • ICML 2020 • Randy Ardywibowo, Shahin Boluki, Xinyu Gong, Zhangyang Wang, Xiaoning Qian
Machine learning (ML) systems often encounter Out-of-Distribution (OoD) errors when dealing with testing data coming from a distribution different from training data.
1 code implementation • ICML 2020 • Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian
We propose a unified framework for adaptive connection sampling in graph neural networks (GNNs) that generalizes existing stochastic regularization methods for training GNNs.
no code implementations • 21 May 2020 • Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian
Semantic hashing has become a crucial component of fast similarity search in many large-scale information retrieval systems, in particular, for text data.
no code implementations • 12 Feb 2020 • Shahin Boluki, Randy Ardywibowo, Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian
In this work, we propose learnable Bernoulli dropout (LBD), a new model-agnostic dropout scheme that considers the dropout rates as parameters jointly optimized with other model parameters.
no code implementations • 1 Nov 2019 • Siamak Zamani Dadaneh, Shahin Boluki, Mingyuan Zhou, Xiaoning Qian
Learning-to-rank methods can generally be categorized into pointwise, pairwise, and listwise approaches.
no code implementations • 26 Feb 2019 • Shahin Boluki, Siamak Zamani Dadaneh, Xiaoning Qian, Edward R. Dougherty
Missing values frequently arise in modern biomedical studies due to various reasons, including missing tests or complex profiling technologies for different omics measurements.