Search Results for author: Saurabh Sinha

Found 6 papers, 2 papers with code

Robust Model-Based Optimization for Challenging Fitness Landscapes

1 code implementation23 May 2023 Saba Ghaffari, Ehsan Saleh, Alexander G. Schwing, Yu-Xiong Wang, Martin D. Burke, Saurabh Sinha

Protein design, a grand challenge of the day, involves optimization on a fitness landscape, and leading methods adopt a model-based approach where a model is trained on a training set (protein sequences and fitness) and proposes candidates to explore next.

Benchmarking Protein Design

CIMLA: Interpretable AI for inference of differential causal networks

no code implementations25 Apr 2023 Payam Dibaeinia, Saurabh Sinha

The discovery of causal relationships from high-dimensional data is a major open problem in bioinformatics.


Entity Set Search of Scientific Literature: An Unsupervised Ranking Approach

1 code implementation29 Apr 2018 Jiaming Shen, Jinfeng Xiao, Xinwei He, Jingbo Shang, Saurabh Sinha, Jiawei Han

Different from Web or general domain search, a large portion of queries in scientific literature search are entity-set queries, that is, multiple entities of possibly different types.

Model Selection

Toward Scalable Machine Learning and Data Mining: the Bioinformatics Case

no code implementations29 Sep 2017 Faraz Faghri, Sayed Hadi Hashemi, Mohammad Babaeizadeh, Mike A. Nalls, Saurabh Sinha, Roy H. Campbell

In an effort to overcome the data deluge in computational biology and bioinformatics and to facilitate bioinformatics research in the era of big data, we identify some of the most influential algorithms that have been widely used in the bioinformatics community.

BIG-bench Machine Learning Clustering +3

Relational Learning and Feature Extraction by Querying over Heterogeneous Information Networks

no code implementations25 Jul 2017 Parisa Kordjamshidi, Sameer Singh, Daniel Khashabi, Christos Christodoulopoulos, Mark Summons, Saurabh Sinha, Dan Roth

In particular, we provide an initial prototype for a relational and graph traversal query language where queries are directly used as relational features for structured machine learning models.

BIG-bench Machine Learning Knowledge Graphs +1

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