SILO Seminar Series

SILO is a weekly seminar series which hosts a catered lunch every Wednesday at the Wisconsin Institute for Discovery for graduate students from across campus. Researchers from Computer Science, Engineering, Mathematics and Statistics make up the core of SILO, but those from other fields are strongly encouraged to participate.

Recent and Upcoming SILOS

SILO Video Archive

7/18/19 | Blake Mason | Learning Nearest Neighbor Graphs from Noisy Distance Samples
7/11/19 | Ardhendu Tripathy | Privacy-Preserving Adversarial Networks
6/27/19 | Harrison Rosenburg | Sample Complexity of Species Tree Estimation From a Linear Combination of Internode Distances
6/20/19 | Silvia Di Gregorio | Chvátal rank in binary polynomial optimization 
6/13/19 | Haley Massa | TBA
5/30/19 | Bryan Van Scoy | Nonconvex Distributed Optimization
5/15/19 | Lalitha Sankar | Information-theoretic Privacy: Leakage measures, robust privacy guarantees, and generative adversarial mechanism design
5/8/19 | Dan Negrut |Billion-degree of freedom Computational Dynamics: from granular flows to 3D printing and on to river fording simulation
5/1/19 | Güzin Bayraksan| Multistage Distributionally Robust Optimization with Total Variation Distance: Modeling and Effective Scenarios
4/24/19 | Guillermo Saipro | Learning Representations for Information Obfuscation and Inference
4/17/19 | Steven Brunton|Data-Driven Discovery and Control of Complex Systems: Uncovering Interpretable and Generalizable Nonlinear Models
4/10/19 | Lav R Varshney|Human-Interpretable Concept Learning via Information Lattices
4/3/19 | Santiago Segarra|Network Inference from Graph Dynamic Processes
3/27/19 | Bradly Stadie | Learning From Sub-Optimal Data
3/13/19 | Brandon Reagen | Hardware Accelerators for Deep Learning: A Proving Ground for Specialized Computing
3/6/19| Lalit Jain | Adaptive Sampling for False Discovery Control
2/27/19 | Dr. Luke Chang | Towards a science of social interactions
2/20/19| Nikolai Matni | Safety and Robustness Guarantees with Learning in the Loop
2/13/19 | Nicolas Garcia Trillos | Large sample asymptotics of spectra of Laplacians and semilinear elliptic PDEs on random geometric graphs.
2/6/19 | AnHai Doan | Entity Matching Meets Data Science: A Progress Report from the Magellan Project
1/30/19 | Jenna Nobles | Using mobile device data to generate population estimates of fertility parameters
1/23/19 | Simon Foucart | Optimal Recovery under Approximability Models, with Applications
12/12/18| Line Roald | Learning Solutions to Constrained Optimization Problems – to Enable a Sustainable Electric Grid
12/5/18| Mohit Gupta | Micro-(Shape-And-Motion)-Scopes
11/28/18| Gauri Joshi  | Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD
11/21/18| Vivak Patel | Statistical Filtering for Optimization over Expectation Operators
11/14/18 | Misha Belkin | Fit without Fear: an Interpolation Perspective on Optimization and Generalization in Modern Machine Learning
11/7/18 | Matus Telgarsky  | Generalization and optimization of deep networks
10/31/18 | Saurabh Gupta | Visual Navigation in 3D Scenes
10/24/18 | Nan Chen | A Conditional Gaussian Framework for Uncertainty Quantification, Data Assimilation and Prediction of Complex Nonlinear Turbulent Dynamical Systems
10/17/18 | Miaoyan Wang | Learning from Binary Multiway Data: Probabilistic Tensor Decomposition and its Statistical Optimality
10/10/18 | Bhuvana Krishnaswamy | Towards an autonomous network of biological sensors
10/3/18 | Mina Karzand | Tight regret bounds for a latent variable model of recommendation systems
09/26/18 | Dr. Lee Seversk & Dr. Eric Heim | Adversarial Networks with Structured Inputs and Output
09/19/18 | Christopher Ryan | Mixed-integer bilevel representability
09/12/18 | Kaibo Lui | Big Data Analytics for Real-time Complex System Monitoring and Prognostics
09/05/18 | Jerry Zhu | How to poison linear regression