Thoughts from

“Women in Machine Learning 2015”

Jayani Withanawasam

About me

● Senior Software Engineer at Zaizi R&D● Author of the book “Apache Mahout Essentials” ● Reading for M.Sc. in Artificial Intelligence at

University of Moratuwa● Graduated from Informatics Institute of

Technology (IIT) ● Summit speaker at Alfresco summit 2014 -

London● Did a poster presentation on “Content Extraction

and Context Inference based Information Retrieval” at WIML 2015 - Montreal

Women in Machine Learning (WiML)● A brief history of WiML

○ Founded in 2006 by,

■ Hanna Wallach - Researcher at Microsoft Research

■ Jenn Wortman Vaughan - Senior Researcher at Microsoft Research

● Objectives

○ Gives female research scientists, and graduate students in the machine

learning community an opportunity to meet, exchange ideas and learn

from each other.

● How I got selected○ Submitted an abstract on machine learning related research project

○ Received travel scholarship to attend the event

○ Zaizi sponsored for conference registration and hotel accommodation

WiML 2015 Sponsors

Content Extraction and Context Inference based Information Retrieval

● Information is embedded as different content forms under varied

contexts

● Problem: Lack of human intuition driven relevance assessment

● Novel approach to retrieve right information, regardless of the content

form or contextual discrepancies

● Use of Bag of Visual Words (BoVW) for visual content and semantic

networks

● Outcome: Set of concept and context descriptors for content

● Applications in search indexing, search ranking, recommendations,

automatic tagging and personalized search

My Poster Presentation

WiML invited talks ● Superhuman Multitasking - Raia Hadsell, Google

DeepMind

■ Games as a platform to implement and test AI applications. E.g., Atari 2600

■ Deep Q Learning (Reinforcement Learning) with model distillation

● Is it all in the Phrasing?

Lillian Lee, Cornell University

○ Does phrasing affects memorability?

WiML invited talks (Continued…)

● Interactive and Interpretable Machine Learning Models for Human Machine Collaboration - Been Kim, AI2/University of Washington

○ Bayes Case Model (BCM)

○ Prototypes and subspaces

● Structured Data - Corinna Cortes, Google Research

○ Structured snippets using good tables

Events I attended

● Facebook Lean In circle

● NVidia deep learning tutorial

○ Demo on DIGITS

● Poster presentations - http://wiml2015.weebly.com/list-of-poster-

presenters.html

● Career/advice session

○ Long-term Career Planning - Lizi Ottens, Apple

○ Work/Life Balance - Amy Greenwald, Brown University

○ Life with Kids - Raia Hadsell, Google DeepMind, Joelle Pineau, McGill

http://wiml2015.weebly.com/list-of-careeradvice-tables.html

http://wiml2015.weebly.com/schedule.html

Neural Information Processing Systems (NIPS)

● Considered as one of the top conference in Machine

Learning

● Some stats:○ 6 invited talks

○ 403 accepted papers (total of 1838 submissions)

● Highlights○ Deep Learning

■ Use of Convolutional Neural Networks (CNNs) in

Computer Vision

■ Use of Recurrent Neural Networks (RNNs) in Natural

Language Processing (NLP)

● LSTMs (Long Short Term Memory Networks)

1. http://academic.research.microsoft.com/RankList?entitytype=3&topDomainID=2&subDomainID=6

Q & A

Thank you