Ashwin Srinivasan
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Ashwin Srinivasan [1]
Ashwin Srinivasan,
an Indian born, Australian-British electrical engineer, computer scientist, and senior professor of computer science at BITS-Pilani, Goa Campus [2], and previously research staff member at IBM India Research Lab [3] [4], New Delhi.
He holds a Ph.D. from University of New South Wales on Non-monotonic logics and their application.
His research interests include symbolic machine learning, inductive logic programming (ILP), implementation of ILP in particular the ILP systems Aleph [5] and P-Progol [6], bioinformatics and chemoinformatics [7].
Contents
ILP and Chess
Abstract from Distinguishing exceptions from noise in non-monotonic Learning [8]:
It is important for a learning program to have a reliable method of deciding whether to treat errors as noise or to include them as exceptions within a growing first-order theory. We explore the use of an information-theoretic measure to decide this problem within the non-monotonic learning framework defined by Closed-World-Specialisation. The approach adopted uses a model that consists of a reference Turing machine which accepts an encoding of a theory and proofs on its input tape and generates the observed data on the output tape. Within this model, the theory is said to `compress' data if the length of the input tape is shorter than that of the output tape. Data found to be incompressible are deemed to be `noise'. We use this feature to implement a compression-guided specialisation procedure that searches for the best-fitting theory for the data (that is, the one with the shortest input tape length). The approach is empirically evaluated on the standard Inductive Logic Programming problem of learning classification rules for the KRK chess endgame.
Selected Publications
1990 ...
- Ashwin Srinivasan, Stephen Muggleton, Michael Bain (1992). Distinguishing exceptions from noise in non-monotonic Learning. ILP92, pdf
- Michael Bain, Ashwin Srinivasan (1995). Inductive logic programming with large-scale unstructured data. Machine Intelligence 14
- Ashwin Srinivasan (1999). A study of two sampling methods for analysing large datasets with ILP. Data Mining and Knowledge Discovery, Vol. 3, No. 1
2000 ...
- Michael Bain, Stephen Muggleton, Ashwin Srinivasan (2000). Generalising Closed World Specialisation: A Chess End Game Application. CitySeerX
- Ashwin Srinivasan (2001, 2007). The aleph manual.
- Ashwin Srinivasan (2002). The Applicability to ILP of Results Concerning the Ordering of Binomial Populations. ILP 2002
- David Page, Ashwin Srinivasan (2003). ILP: A Short Look Back and a Longer Look Forward. Journal of Machine Learning Research, Vol. 4, pdf
- Ashwin Srinivasan (2005). Five Problems in Five Areas for Five Years. ILP 2005
2010 ...
- Stephen Muggleton, Luc De Raedt, David Poole, Ivan Bratko, Peter A. Flach, Katsumi Inoue, Ashwin Srinivasan (2012). ILP turns 20 - Biography and future challenges. Machine Learning, Vol. 86, No. 1
- Ashwin Srinivasan, Lovekesh Vig, Michael Bain (2018). Logical Explanations for Deep Relational Machines Using Relevance Information. arXiv:1807.00595
- Michael Bain, Ashwin Srinivasan (2018). Identification of biological transition systems using meta-interpreted logic programs. Machine Learning, Vol. 107, No. 7 [10]
External Links
References
- ↑ Ashwin Srinivasan at IBM
- ↑ Ashwin Srinivasan - Google Scholar Citations
- ↑ Ashwin Srinivasan - Curriculum Vitae
- ↑ IBM Research – India
- ↑ Ashwin Srinivasan (2001, 2007). The aleph manual.
- ↑ PROGOL (OxUni)
- ↑ Applications and Datasets
- ↑ Ashwin Srinivasan, Stephen Muggleton, Michael Bain (1992). Distinguishing exceptions from noise in non-monotonic Learning. ILP92
- ↑ dblp: Ashwin Srinivasan
- ↑ Operational semantics from Wikipedia
