When: October 28, 2015, 12:30 PM
Location: 3rd Floor Orchard View Room , Discovery Building
Contact: 608-316-4401, firstname.lastname@example.org
Statistical Inference of Phylogenetic Networks
Bacteria and other organisms do not follow the paradigm of vertical inheritance of genetic material. Human beings, for example, inherit their DNA from their parents only (vertical transfer), but bacteria can share DNA between different species (horizontal transfer). Therefore, their evolution cannot be modeled by a tree. To incorporate these organisms to the tree of life, we need methods to infer phylogenetic networks. In this talk, I will present a statistical method to infer phylogenetic networks from DNA sequences. I will discuss the challenges and results on the identifiability and the optimization of the model.
Our techniques to learn phylogenetic networks will enable scientists to incorporate organisms to the tree of life in parts that are more net-like than tree-like, and thus, complete a broader picture of evolution.
Efficient and Parsimonious Agnostic Active Learning
We develop a new active learning algorithm for the streaming setting satisfying three important properties:
1) It probably works for any classifier representation and classification problem including those with severe noise.
2) It is efficiently implementable with an ERM oracle.
3) It is more aggressive than all previous approaches satisfying 1 and 2.
To do this we create an algorithm based on a newly defined optimization problem and analyze it. We also conduct the first experimental analysis of all efficient agnostic active learning algorithms, evaluating their strengths and weaknesses in different settings.
This is joint work with Alekh Agarwal, John Langford and Rob Schapire at Microsoft Research, and Daniel Hsu at Columbia University.
SILO is a lecture series with speakers from the UW faculty, graduate students or invited researchers that discuss mathematical related topics. The seminars are organized by WID’s Optimization research group.
SILO’s purpose is to provide a forum that helps connect and recruit mathematically-minded graduate students. SILO is a lunch-and-listen format, where speakers present interesting math topics while the audience eats lunch.