Aditya Krishna Menon

PhD candidate, Computer Science and Engineering
University of California, San Diego
EBU3B 4144

About me

I'm a 6th year PhD student here at UCSD, working on machine learning with Prof. Charles Elkan. I did my undergrad at the University of Sydney, where I got an Honours degree in Computer Science. Much before life as a university student, I went to school in India, where I was born and grew up. Here is a copy of my CV.

You can contact me by email: akmenon followed by

Research interests

My PhD research is on dyadic prediction: this is the problem of predicting outcomes arising from the interaction of pairs of entities. Two important special cases of this problem are collaborative filtering (popularized by the Netflix prize), and link prediction in graphs. Some others areas that I have worked on include random projections, approximations to the singular value decomposition, and large-scale support vector machines. I have also spent several months studying the basics of game theory, which arises in many more places than one might think. In general, I respond to problems that have an underlying mathematical elegance and simplicity.



A Colorful Approach to Text Processing by Example. Kuat Yessenov, Shubham Tulsiani, Aditya Menon, Robert C. Miller, Sumit Gulwani, Butler Lampson, and Adam Kalai. In Proceedings of the 26th annual ACM Symposium on User Interface Software and Technology (UIST) 2013.

Beam Search Algorithms for Multilabel Learning. Abhishek Kumar, Shankar Vembu, Aditya Krishna Menon, and Charles Elkan. In Machine Learning, 2013. [pdf]

Inappropriate Access Detection for Electronic Health Records Using Collaborative Filtering. Aditya Krishna Menon, Xiaoqian Jiang, Jihoon Kim, Lucila Ohno-Machado, and Jaideep Vaidya. In Machine Learning, Special Issue on Machine Learning for Society, 2013. [pdf]

On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance. Aditya Krishna Menon, Harikrishna Narasimhan, Shivani Agarwal and Sanjay Chawla. In International Conference on Machine Learning (ICML), 2013. [pdf]

A Machine Learning Framework for Programming by Example. Aditya Krishna Menon, Omer Tamuz, Sumit Gulwani, Butler Lampson, and Adam Tauman Kalai. In International Conference on Machine Learning (ICML), 2013. [pdf]


Learning and Inference in Probabilistic Classifier Chains with Beam Search. Abhishek Kumar, Shankar Vembu, Aditya Krishna Menon, and Charles Elkan. In Machine Learning and Knowledge Discovery in Databases - European Conference (ECML-PKDD), Proceedings Part I, 2012. [pdf]

Doubly Optimized Calibrated Support Vector Machine (DOC-SVM): an algorithm for Joint Optimization of Discrimination and Calibration. Xiaoqian Jiang, Aditya Krishna Menon, Shuang Wang, Jihoon Kim, and Lucila Ohno-Machado. In PLoS ONE, 7(11): e48823, 2012. [link]

Predicting accurate probabilities with a ranking loss. Aditya Krishna Menon, Xiaoqian Jiang, Shankar Vembu, Charles Elkan, and Lucila Ohno-Machado. In International Conference on Machine Learning (ICML) 2012. [pdf]


Link prediction via matrix factorization. Aditya Krishna Menon, Charles Elkan. In Machine Learning and Knowledge Discovery In Databases - European Conference, ECML-PKDD, Proceedings Part II, 2011. [pdf]

Response prediction using collaborative filtering with hierarchies and side-information. Aditya Krishna Menon, Krishna-Prasad Chitrapura, Sachin Garg, Deepak Agarwal, and Nagaraj Kota. In Knowledge Discovery and Data Mining (KDD), San Diego, California, 2011. [pdf] [slides] [poster] [sample code]


Fast algorithms for approximating the singular value decomposition. Aditya Krishna Menon, Charles Elkan. To appear in Transactions of Knowledge and Data Discovery: Special Issue on Large-Scale Data Mining (TKDD-LDMTA), 2010. [pdf] [code]

A log-linear model with latent features for dyadic prediction. Aditya Krishna Menon, Charles Elkan. In IEEE International Conference on Data Mining (ICDM), Sydney, Australia, 2010. [pdf] [slides] [code]

Predicting labels for dyadic data. Aditya Krishna Menon, Charles Elkan. In Data Mining and Knowledge Discovery: Special Issue on Papers from ECML-PKDD, Volume 21, Number 2, 2010. [pdf] [slides]


An incremental data-stream sketch using sparse random projections. Aditya Krishna Menon, Gia Vinh Anh Pham, Sanjay Chawla and Anastasios Viglas. In Proceedings of the 2007 SIAM conference on data mining (SDM), Minnesota, USA. [pdf].

Other papers

Large-Scale Support Vector Machines: Algorithms and Theory. Aditya Krishna Menon. Research Exam, University of California, San Diego. 2009. [pdf] [slides].

An incremental data-stream sketch using sparse random projections. Aditya Krishna Menon, Gia Vinh Anh Pham, Sanjay Chawla and Anastasios Viglas. Technical Report 609, The University of Sydney. 2007. [pdf].

Random projections and applications to dimensionality reduction. Aditya Krishna Menon. Honours thesis, The University of Sydney. 2006. [pdf] [slides].


Below are a number of talks and presentations I have given, usually on the results of a paper I have read. Please note that these are based on my own understanding of the material, and have not been subjected to much external scrutiny; hence, they may contain errors.

CSE291B talk: Very Sparse Random Projections by Ping Li, Trevor Hastie and Kenneth Church, KDD '06. March 2009. [pdf].

CSE291 talk: Estimation of the Click Volume by Large Scale Regression Analysis by Yuri Lifshits and Dirk Nowotka, CSR '07. May 2008. [pdf].

CSE291 talk: Adversarial Classification by Nilesh Dalvi, Pedro Domingos, Mausam, Sumit Sanghai and Deepak Verma. May 2008. [pdf].

NICTA talk: Fast Dimension Reduction Using Rademacher Series on Dual BCH Codes by Nir Ailon and Edo Liberty, SODA 2008. August 2007. [pdf].

INFO4011 presentation: Nash equilibria: complexity and computation. August 2007. [pdf].

Algorithms reading group talk: Computing Nash equilibria in 2-player games and beyond. June 2007. [pdf].


A list of the various courses that I've taken at UCSD.
Fall 2007
CSE120, Operating Systems
CSE141, Computer Architecture
CSE200, Computability and Complexity

Winter 2008
CSE130, Programming Languages
CSE221, Operating Systems
CSE240, Computer Architecture

Spring 2008
CSE202, Algorithms
CSE205A, Logic in Computer Science
CSE291, Web-scale information retrieval and data mining

Fall 2008
CSE250A, Principles of AI: Probabilistic Reasoning
CSE250B, Principles of AI: Learning

Winter 2009
CSE232, Database System Implementation
CSE291B, Unsupervised Learning
TA: CSE101, Algorithms

Spring 2009
ECE273, Convex Optimization

Fall 2009
CSE207, Modern Cryptography

Winter 2010
TA: CSE250B, Principles of AI: Learning

Other interests

Starting with the obvious, I have had an intense passion for programming for nearly as long as I can remember. I grew up coding in QBasic, but have now settled (stagnated?) on Python, Java, and very occasionally, C++. For nearly half the period I have spent programming, I have been interested in creating a full-fledged (albeit simple) game. I have never succeeded to my satisfaction, but have been through several iterations of Tetris, PacMan and Breakout. Creating a basic RPG has been a perpetual dream!

Perhaps unsurprisingly, given my interests in game programming, I am very fond of classic-era PC games. I have spent many hours on the first wave of adventure games, such as those by Sierra and LucasArts. My two all time favourites are Ultima VII, an RPG whose depth and scope I have never seen equalled, and King's Quest VI, the finest adventure game ever made. Among more modern games, my taste is towards (western) RPGs, such as the Baldur's Gate series. I am always interested in developments that push gaming into becoming a more serious medium.

The biggest non-technical passion in my life is music, with a bias towards popular song in the period from roughly '65 - '75. Consequently, I still believe in the idea of an album serving as an artistic statement! While my favourites in this period consist of the obvious - The White Album and Blonde on Blonde - they include slightly more obscure albums such as Ram and For Your Pleasure.

I enjoy reading immensely, although I have not made enough time for this in the past few years. I typically read fiction, with a focus on works that have a slight philosophical tinge. I have made some attempts to write in a similar vein, but have only been successful in a short story format. Three favourite books are Graham Greene's The Heart of the Matter, Herman Hesse's Narziss and Goldmund, and Aldous Huxley's Eyeless in Gaza, all of which I unconditionally recommend!

Finally, I think that cricket is probably the greatest sport in the world. While I do not have as much time as I once did to watch a match of test cricket, I find that a particularly good series still manages to grip me for days on end. If ever sport could be considered art, it would be in the form of a good test match!

© Last updated on May 29 2013 by Aditya Menon