NeurIPS 2019
This year marks the 33rd annual Conference on Neural Information Processing Systems, a workshop and conference hosted by the Neural Information Processing Systems Foundation that is more casually referred to as NeurIPS. The accepted papers for NeurIPS 2019 were posted earlier this month, and it gave CAIDA a lot to celebrate. The University of British Columbia has 15 individuals featured across 9 of the accepted papers, and 6 of CAIDA’s members have papers that have been accepted. This is just another exciting way that the research done by CAIDA’s members is contributing to the scientific world. You can see the titles of the papers by our members below, and you can check out the rest of the accepted papers here.
Trevor Campbell
Universal Boosting Variational Inference
Sparse Variational Inference: Bayesian Coresets from Scratch
Kevin Leyton-Brown
Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration
Mark Schmidt
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates
Frank Wood
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
The Thermodynamic Variational Objective
Maryam Kamgarpour (joining ECE at UBC in January)
No-Regret Learning in Unknown Games with Correlated Payoffs
Margo Seltzer
Optimal Sparse Decision Trees