Learning Graphical Models
The Description Length of Deep Learning models
Neural Information Processing Systems http://nips.cc/
A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families
Brian Axelrod, Ilias Diakonikolas, Alistair Stewart, Anastasios Sidiropoulos, Gregory Valiant
Neural Information Processing Systems http://nips.cc/
On Certified Generalization in Structured Prediction
Structured prediction is the task of predicting an output which itself contains internal structure. As an example, consider the problem of image segmentation.
This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization
Bayesian Optimization (BO) is an effective framework for black-box optimization.
Fast Structured Decoding for Sequence Models
Zhiqing Sun, Zhuohan Li, Haoqing Wang, Di He, Zi Lin, Zhihong Deng
Neural Information Processing Systems http://nips.cc/
GSLB: The Graph Structure Learning Benchmark Zhixun Li1 Liang Wang 2,3 Xin Sun 4 Yifan Luo
Specifically, GSLB systematically investigates the characteristics of GSL in terms of three dimensions: effectiveness, robustness, and complexity .
Multi-value Rule Sets for Interpretable Classification with Feature-Efficient Representations
Neural Information Processing Systems http://nips.cc/
