Industry
A Block Coordinate Ascent Algorithm for Mean-Variance Optimization
Tengyang Xie, Bo Liu, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon
Risk management in dynamic decision problems is a primary concern in many fields, including financial investment, autonomous driving, and healthcare.
ClimbQ: Class Imbalanced Quantization Enabling Robustness on Efficient Inferences Ting-An Chen 1,2, De-Nian Y ang 2,3 Ming-Syan Chen 1,3 1
Despite a realistic problem, quantization on class-imbalanced data has not been studied.
Causal Effect Identification in a Sub-Population with Latent Variables Amir Mohammad Abouei
Causal inference, i.e., understanding the effect of an intervention in a stochastic system, is a key focus of research in statistics and machine learning [
Change-pointDetectionforSparseandDense FunctionalDatainGeneralDimensions
We study the problem of change-point detection and localisation for functional data sequentially observed on a generald-dimensional space, where we allow thefunctional curvestobeeither sparsely ordensely sampled.
Gamma-Poisson Dynamic Matrix Factorization Embedded with Metadata Influence
Trong Dinh Thac Do, Longbing Cao
Neural Information Processing Systems http://nips.cc/
Actively Testing Y our Model While It Learns: Realizing Label-Efficient Learning in Practice Dayou Yu
In active learning (AL), we focus on reducing the data annotation cost from the model training perspective. However, "testing", which often refers to the model
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
Conditional sampling is an essential primitive in the machine learning toolkit.
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
Conditional sampling is an essential primitive in the machine learning toolkit.
Random Path Selection for Continual Learning
Jathushan Rajasegaran, Munawar Hayat, Salman H. Khan, Fahad Shahbaz Khan, Ling Shao
Neural Information Processing Systems http://nips.cc/