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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
About me
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Posts
Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
Portfolio item number 1
Published:
Short description of portfolio item number 1
Portfolio item number 2
Published:
Short description of portfolio item number 2
publications
Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Embeddings
Published in IJCAI 2020, 2019
Recommended citation: Mennatullah Siam*, Naren Doraiswamy*, Boris Oreshkin*, Hengshuai Yao, Martin Jagersand.(2019). Accepted in IJCAI 2020.
One-Shot Weakly Supervised Video Object Segmentation
Published in ICLR PML4DC Workshop 2020, 2019
Recommended citation: Mennatullah Siam*, Naren Doraiswamy*, Boris Oreshkin*, Hengshuai Yao, Martin Jagersand. (2019).Accepted in ICLR 2020 PML4DC Workshop. ICLR 2020
Improving Semi-Supervised domain adaptation using effective target selection and semantics.
Published in CVPR L2ID workshop 2021, 2020
Recommended citation: Anurag Singh*, Naren Doraiswamy*, Sawa Takamuku, Megh Bhalerao, Titir Dutta, Soma Biswas, Aditya Chepuri, Balasubramanian Vengatesan, Naotake Natori.CVPR L2ID Workshop 2021.
talks
Application of Machine learning algorithms to component modelling systems
Published:
A talk on the application of machine learning algorithms in building efficient component models.
Talk on interpreting black box predictions via influence functions
Published:
Gave a brief lecture on interpreting black box predictions via influence functions as part of the Science of Deep Learning course taught by Prof. Wei Hu. Slides
Lecture on Naive Bayes and Decision Trees algorithms
Published:
Gave an extensive 2 hour lecture on Naive Bayes and Decision tree algorithms as part of the teaching staff of SI 568 course. Slides
Talk on label free membership inference attacks.
Published:
Gave a brief lecture on the developments of label-free membership inference attack as part of the Adversarial Machine learning course. Slides
teaching
AI Instructor Nurture.ai Bootcamp
Nurture.ai, Nvidia office, 2018
I along with a group of 5 people taught deep learning to a bunch of 50 AI enthusiasts ranging from undergrad students to data scientists in the city during weekends.
Deep learning mentor
Udacity Nanodegrees, Online, 2020
I provided 1:1 mentoring sessions for students enrolled in the Udacity School of AI nanodegrees. Personally mentored over 30 students in a span of two and a half years.
Graduate Student Instructor - SI 671/721
GSI for SI 671/721, School of Information, University of Michigan, Ann Arbor, 2022
I am a graduate student instructor for the advanced graduate level course SI 671/721 at the school of Information. I lead the discussion sections, office hours and grade the weekly assignments. Received a 100% tuition waiver for the position.
Graduate Student Instructor - SI 568
GSI for SI 568, School of Information, University of Michigan, Ann Arbor, 2023
I am serving as a graduate student instructor for the graduate course SI 568 at the school of Information. I take weekly classes while I also lead the discussion sections, office hours and grade the weekly assignments. Received a 100% tuition waiver for the position.
