IFDS

IFDS Ideas Forum-Greg Canal
2021-09-27 12:30 - 13:30 (America/Chicago) | Orchard View Room, 330 N. Orchard Street, 3rd Floor NE, Madison, Wisconsin, 53715, United States
UNTIL FURTHER NOTICE: Seminars are hybrid in-person and via zoom.

SILO-Jeff Linderoth
2021-09-29 12:30 (America/Chicago)
Subspace cluster with missing data via integer programming

IFDS Ideas Forum-Chaobing Song
2021-10-04 13:30 - 14:00 (America/Chicago) | Orchard View Room, 330 N. Orchard Street, 3rd Floor NE, Madison, Wisconsin, 53715, United States

SILO-TBA
2021-10-06 12:30, 2021-10-13 12:30 (America/Chicago)

IFDS All-Hands: Qin Li
2021-10-08 13:30 - 14:30 (America/Los_Angeles)
Title:
Mean field theory in Inverse Problems from Bayesian inference to overparameterization of networks

Abstract:
Bayesian sampling and neural networks are seemingly two different machine learning areas, but they both deal with many particle systems. In sampling, one evolves a large number of samples (particles) to match a target distribution function, and in optimizing over-parameterized neural networks, one can view neurons particles that feed each other information in the DNN flow. These perspectives allow us to employ mean-field theory, a powerful tool that translates dynamics of many particle system into a partial differential equation (PDE), so rich PDE analysis techniques can be used to understand both the convergence of sampling methods and the zero-loss property of over-parameterization of ResNets. We showcase the use of mean-field theory in these two machine learning areas, and we also invite the audience to brainstorm other possible applications.

IFDS Ideas Forum-Multilingual NLP: Zero-shot Cross-lingual Transfer Learning
2021-10-11 12:30 - 13:00 (America/Chicago) | Orchard View Room, 330 N. Orchard Street, 3rd Floor NE, Madison, Wisconsin, 53715, United States

IFDS Ideas Forum: TBD
2021-10-18 12:30 - 13:00 (America/Chicago) | Zoom
REMOTE only

E & A SIG:
2021-10-20 12:00 - 13:00, 2021-11-17 12:00 - 13:00, 2021-12-15 12:00 - 13:00 (America/Los_Angeles)

SILO-Josiah Hanna
2021-10-20 12:30 (America/Chicago)

IFDS Ideas Forum-Zhiyan Ding
2021-10-25 12:30 - 13:00 (America/Chicago) | Orchard View Room, 330 N. Orchard Street, 3rd Floor NE, Madison, Wisconsin, 53715, United States
Different regimes of overparameterized neural network: NTK and mean-field limit
UNTIL FURTHER NOTICE: Seminars are hybrid in-person and via zoom.

SILO-Hanie Sedghi
2021-10-27 12:30 (America/Chicago)

ML-Opt@UW Stephen Mussmann
2021-10-29 13:30 - 14:30 (America/Los_Angeles)
Understanding and analyzing the effectiveness of uncertainty sampling

Active learning techniques attempt to reduce the amount of data required to learn a classifier by leveraging adaptivity. In particular, an algorithm iteratively selects and labels points from an unlabeled pool of data points. Over the history of active learning, many algorithms have been developed, though one heuristic algorithm, uncertainty sampling, stands out by its popularity, effectiveness, simplicity, and intuitiveness. Despite this, uncertainty sampling has known failure modes and lacks the theoretical underpinnings of some other algorithms such as those based on disagreement. Here, we present a few analyses of uncertainty sampling. First, we find that uncertainty sampling iterations implicitly optimizes the (generally non-convex) zero-one loss, explaining how uncertainty sampling can achieve lower error than labeling the entire unlabeled pool and highlighting the importance of a good initialization. Second, for logistic regression, we show that the extent to which uncertainty sampling outperforms random sampling is inversely proportional to the asymptotic error, both theoretically and empirically. Finally, we use the previous insights to show uncertainty sampling works very well on a particular NLP task due to extreme label imbalance. Taken together, these results provide a sturdier foundation for understanding and using uncertainty sampling.

https://washington.zoom.us/j/99919016373?pwd=[REDACTED]

IFDS Ideas Forum-Hanbaek Lyu
2021-11-01 12:30 - 13:00 (America/Chicago) | Orchard View Room, 330 N. Orchard Street, 3rd Floor NE, Madison, Wisconsin, 53715, United States

SILO-Sebastien Roch
2021-11-03 12:30 (America/Chicago)

IFDS All-Hands: Kevin Jamieson
2021-11-05 13:30 - 14:30 (America/Los_Angeles)
Title: Instance Dependent Sample Complexity Bounds for Interactive Learning

Abstract: The sample complexity of an interactive learning problem, such as multi-armed bandits or reinforcement learning, is the number of interactions with nature required to output an answer (e.g., a recommended arm or policy) that is approximately close to optimal with high probability. While minimax guarantees can be useful rules of thumb to gauge the difficulty of a problem class, algorithms optimized for this worst-case metric often fail to adapt to “easy” instances where fewer samples suffice. In this talk, I will highlight some of my group’s work on algorithms that obtain optimal, finite time, instance dependent sample complexities that scale with the true difficulty of the particular instance, versus just the worst-case. In particular, I will describe a unifying experimental design based approach used to obtain such algorithms for best-arm identification for linear bandits, contextual bandits with arbitrary policy classes, and smooth losses for linear dynamical systems.

Kevin’s website: https://homes.cs.washington.edu/~jamieson/about.html

Zoom link: contact organizer

(The talk will not be recorded, we hope you can join us live!)

IFDS Ideas Forum-Sushrut Karmalkar
2021-11-08 12:30 - 13:00 (America/Chicago) | Orchard View Room, 330 N. Orchard Street, 3rd Floor NE, Madison, Wisconsin, 53715, United States

SILO-Qiaomin Xie
2021-11-10 12:30 (America/Chicago)

IFDS Ideas Forum-Jeffrey Covington
2021-11-15 12:30 - 13:00 (America/Chicago) | Orchard View Room, 330 N. Orchard Street, 3rd Floor NE, Madison, Wisconsin, 53715, United States

SILO-Keith Levin
2021-11-17 12:30 (America/Chicago)

IFDS Ideas Forum-Yuchen Zeng & Liu Yang
2021-11-22 12:30 - 13:00 (America/Chicago) | Orchard View Room, 330 N. Orchard Street, 3rd Floor NE, Madison, Wisconsin, 53715, United States

SILO-Yudong Chen
2021-11-24 12:30 (America/Chicago)

IFDS Ideas Forum-Sijia Fang & Yuetian Luo
2021-11-29 12:30 - 13:00 (America/Chicago) | Orchard View Room, 330 N. Orchard Street, 3rd Floor NE, Madison, Wisconsin, 53715, United States

SILO-Jerry Zhu
2021-12-01 12:30 (America/Chicago)

IFDS All-Hands: Marcella Gomez, UCSC Applied Math
2021-12-03 13:30 - 14:30 (America/Los_Angeles)
Title: Open problems in mathematical modeling and control of wound healing
Abstract: Wound healing consists of a series of overlapping biological process with sophisticated coordination to promote wound closure. Our research work currently focuses on the task of accelerating wound healing by targeting and artificially manipulating key biological processes. In particular, we aim to develop models and control architectures for real-time feedback control for accelerated wound closure. In this talk, I discuss the progress and challenges of working with a complex biological process with limited data, as well as, developing feedback control algorithms for systems interfaced with a bioelectronic device and limited observable states.
Bio: Marcella M. Gomez is an associate professor at UC Santa Cruz in the department of Applied Mathematics. She received her PhD from Caltech in 2015 and a B.S. from UC Berkeley in 2009; both degrees in Mechanical Engineering. Her research interests are in synthetic and systems biology. In particular, she is interested in developing data-driven methods and foundations for modeling and control of complex biological systems.
Zoom link via email or contact organizer.

IFDS Ideas Forum-Julian Katz-Samuels
2021-12-06 12:30 - 13:00 (America/Chicago) | Orchard View Room, 330 N. Orchard Street, 3rd Floor NE, Madison, Wisconsin, 53715, United States

SILO-Jose Miguel Ponciano
2021-12-08 12:30 (America/Chicago)

IFDS Ideas Forum-Max Bacharach
2021-12-13 12:30 - 13:00 (America/Chicago) | Orchard View Room, 330 N. Orchard Street, 3rd Floor NE, Madison, Wisconsin, 53715, United States
