Paper Summary - Assessing the Local Interpretability of Machine Learning Models by Slack et. al. (2019)
Summarizing and providing my notes on the paper - Assessing the Local Interpretability of Machine Learning Models by Slack et. al. (2019)
- paper-summary 12
- xrl-technique 7
- research 3
- deep-dive 3
- video-summary 3
- competitive-programming 2
- codechef 2
- personal 2
- xrl 2
- summary 1
- nov19b 1
- dec19a 1
- python 1
- knexus 1
- intern 1
- xai 1
- interpretability 1
- paper-summary, 1
- hierarchical-rl 1
- advice 1
- biases 1
- breaking-bad 1
- graphs 1
- maximum-matching 1
paper-summary
Paper Summary - A review of possible effects of cognitive biases on interpretation of rule-based machine learning models by Kliegr, Bahník and Fürnkranz (2021)
Summarizing and providing my notes on the paper - A review of possible effects of cognitive biases on interpretation of rule-based machine learning models by...
Paper Summary - Synthesizing Interpretable Strategies for Solving Puzzle Games by Butler, Torlak & Popović (2017)
Summarizing and providing my notes on the paper - Synthesizing Interpretable Strategies for Solving Puzzle Games by Butler, Torlak & Popović (2017)
Paper Summary - Programmatically Interpretable Reinforcement Learning by Verma et. al. (2018)
Summarizing and providing my notes on the paper - Programmatically Interpretable Reinforcement Learning by Verma et. al. (2018)
Paper Summary - Distilling Deep Reinforcement Learning Policies in Soft Decision Trees by Coppens et. al. (2019)
Summarizing and providing my notes on the paper - Distilling Deep Reinforcement Learning Policies in Soft Decision Trees by Coppens et. al. (2019)
Paper Summary - Contrastive explanations for reinforcement learning in terms of expected consequences by van der Waa et. al. (2018)
Summarizing and providing my notes on the paper - Contrastive explanations for reinforcement learning in terms of expected consequences by van der Waa et. a...
Paper Summary - Graying the black box: Understanding DQNs by Zahavy, Ben-Zrihem & Mannor (2016)
Summarizing and providing my notes on the paper - Graying the black box: Understanding DQNs by Zahavy, Ben-Zrihem & Mannor (2016)
Paper Summary - Improving Robot Controller Transparency Through Autonomous Policy Explanation by Hayes & Shah (2017)
Summarizing and providing my notes on the paper - Improving Robot Controller Transparency Through Autonomous Policy Explanation by Hayes & Shah (2017)
Paper Summary - Policy Distillation by Rusu et. al. (2016)
Summarizing and providing my notes on the paper - Policy Distillation by Rusu et. al. (2016)
Paper Summary - Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees by Liu et. al. (2018)
Summarizing and providing my notes on the paper - Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees by Liu et. al. (2018)
Paper Summary - Explainable Reinforcement Learning Through a Causal Lens by Madumal et. al. (2020)
Summarizing and providing my notes on the paper - Explainable Reinforcement Learning Through a Causal Lens by Madumal et. al. (2020)
Paper Summary - An Evaluation of the Human-Interpretability of Explanation by Lage et. al. (2019)
Summarizing and providing my notes on the paper - An Evaluation of the Human-Interpretability of Explanation by Lage et. al. (2019)
xrl-technique
Paper Summary - Programmatically Interpretable Reinforcement Learning by Verma et. al. (2018)
Summarizing and providing my notes on the paper - Programmatically Interpretable Reinforcement Learning by Verma et. al. (2018)
Paper Summary - Distilling Deep Reinforcement Learning Policies in Soft Decision Trees by Coppens et. al. (2019)
Summarizing and providing my notes on the paper - Distilling Deep Reinforcement Learning Policies in Soft Decision Trees by Coppens et. al. (2019)
Paper Summary - Contrastive explanations for reinforcement learning in terms of expected consequences by van der Waa et. al. (2018)
Summarizing and providing my notes on the paper - Contrastive explanations for reinforcement learning in terms of expected consequences by van der Waa et. a...
Paper Summary - Graying the black box: Understanding DQNs by Zahavy, Ben-Zrihem & Mannor (2016)
Summarizing and providing my notes on the paper - Graying the black box: Understanding DQNs by Zahavy, Ben-Zrihem & Mannor (2016)
Paper Summary - Improving Robot Controller Transparency Through Autonomous Policy Explanation by Hayes & Shah (2017)
Summarizing and providing my notes on the paper - Improving Robot Controller Transparency Through Autonomous Policy Explanation by Hayes & Shah (2017)
Paper Summary - Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees by Liu et. al. (2018)
Summarizing and providing my notes on the paper - Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees by Liu et. al. (2018)
Paper Summary - Explainable Reinforcement Learning Through a Causal Lens by Madumal et. al. (2020)
Summarizing and providing my notes on the paper - Explainable Reinforcement Learning Through a Causal Lens by Madumal et. al. (2020)
research
Video Summary - Human-AI Co-creation for Games and Game Creators by Mikhail Jacob (2021)
Summarizing and providing my notes on the research talk - Human-AI Co-creation for Games and Game Creators by Mikhail Jacob (2021)
Video Summary - Designer-friendly Machine Learning and Reinforcement Learning for Video Games by Adith Swaminathan & Brian Broll (2021)
Summarizing and providing my notes on the research talk - Designer-friendly Machine Learning and Reinforcement Learning for Video Games by Adith Swaminathan ...
My First Publication
A retrospective on the problem-solving path that led to my first publication.
deep-dive
My Internship at Knexus Research
A retrospective of my time interning with Knexus Research, the problem I solved, and what I learned
Integer Objects in Python
An investigation into a curious implementataion detail of Python integer objects, and a quantitative explanation of the choices behind it.
My First Publication
A retrospective on the problem-solving path that led to my first publication.
video-summary
Video Summary - Human-AI Co-creation for Games and Game Creators by Mikhail Jacob (2021)
Summarizing and providing my notes on the research talk - Human-AI Co-creation for Games and Game Creators by Mikhail Jacob (2021)
Video Summary - Designer-friendly Machine Learning and Reinforcement Learning for Video Games by Adith Swaminathan & Brian Broll (2021)
Summarizing and providing my notes on the research talk - Designer-friendly Machine Learning and Reinforcement Learning for Video Games by Adith Swaminathan ...
Video Summary - How to write a great research paper by Simon Peyton Jones (2016)
Summarizing and providing my notes on the talk - How to write a great research paper by Simon Peyton Jones (2016)
competitive-programming
Codechef December 2019 Long Contest (Div. 1)
An editorial for the Dec ‘19 Div. 1 long contest on Codechef.
Codechef November 2019 Long Contest (Div. 2)
An editorial for the Nov ‘19 Div. 2 long contest on Codechef.
codechef
Codechef December 2019 Long Contest (Div. 1)
An editorial for the Dec ‘19 Div. 1 long contest on Codechef.
Codechef November 2019 Long Contest (Div. 2)
An editorial for the Nov ‘19 Div. 2 long contest on Codechef.
personal
My Internship at Knexus Research
A retrospective of my time interning with Knexus Research, the problem I solved, and what I learned
My First Publication
A retrospective on the problem-solving path that led to my first publication.
xrl
Paper Summary - A review of possible effects of cognitive biases on interpretation of rule-based machine learning models by Kliegr, Bahník and Fürnkranz (2021)
Summarizing and providing my notes on the paper - A review of possible effects of cognitive biases on interpretation of rule-based machine learning models by...
Paper Summary - Policy Distillation by Rusu et. al. (2016)
Summarizing and providing my notes on the paper - Policy Distillation by Rusu et. al. (2016)
summary
Notes: Q&A by Gayle Laakman McDowell
My notes from the Q&A by Gayle Laakman McDowell on Acing Programming Interviews
nov19b
Codechef November 2019 Long Contest (Div. 2)
An editorial for the Nov ‘19 Div. 2 long contest on Codechef.
dec19a
Codechef December 2019 Long Contest (Div. 1)
An editorial for the Dec ‘19 Div. 1 long contest on Codechef.
python
Integer Objects in Python
An investigation into a curious implementataion detail of Python integer objects, and a quantitative explanation of the choices behind it.
knexus
My Internship at Knexus Research
A retrospective of my time interning with Knexus Research, the problem I solved, and what I learned
intern
My Internship at Knexus Research
A retrospective of my time interning with Knexus Research, the problem I solved, and what I learned
xai
Paper Summary - An Evaluation of the Human-Interpretability of Explanation by Lage et. al. (2019)
Summarizing and providing my notes on the paper - An Evaluation of the Human-Interpretability of Explanation by Lage et. al. (2019)
interpretability
Paper Summary - An Evaluation of the Human-Interpretability of Explanation by Lage et. al. (2019)
Summarizing and providing my notes on the paper - An Evaluation of the Human-Interpretability of Explanation by Lage et. al. (2019)
paper-summary,
Paper Summary - Hierarchical and Interpretable Skill Acquisition in Multi-Task Reinforcement Learning by Shu, Xiong & Socher (2017)
Summarizing and providing my notes on the paper - Hierarchical and Interpretable Skill Acquisition in Multi-Task Reinforcement Learning by Shu, Xiong & S...
hierarchical-rl
Paper Summary - Hierarchical and Interpretable Skill Acquisition in Multi-Task Reinforcement Learning by Shu, Xiong & Socher (2017)
Summarizing and providing my notes on the paper - Hierarchical and Interpretable Skill Acquisition in Multi-Task Reinforcement Learning by Shu, Xiong & S...
advice
Video Summary - How to write a great research paper by Simon Peyton Jones (2016)
Summarizing and providing my notes on the talk - How to write a great research paper by Simon Peyton Jones (2016)
biases
Paper Summary - A review of possible effects of cognitive biases on interpretation of rule-based machine learning models by Kliegr, Bahník and Fürnkranz (2021)
Summarizing and providing my notes on the paper - A review of possible effects of cognitive biases on interpretation of rule-based machine learning models by...
breaking-bad
Elementalizing Names for Breaking Bad
Attempting to use bipartite graphs to help Breaking Bad with its unique opening credits.
graphs
Elementalizing Names for Breaking Bad
Attempting to use bipartite graphs to help Breaking Bad with its unique opening credits.
maximum-matching
Elementalizing Names for Breaking Bad
Attempting to use bipartite graphs to help Breaking Bad with its unique opening credits.