Asia
Global Identifiability of ℓ 1-based Dictionary Learning via Matrix Volume Optimization
On the theory side, most of the existing works have focused on algorithm design.
Global Identifiability of ℓ 1-based Dictionary Learning via Matrix Volume Optimization
On the theory side, most of the existing works have focused on algorithm design.
Statistical mechanics of low-rank tensor decomposition
Jonathan Kadmon, Surya Ganguli
Neural Information Processing Systems http://nips.cc/
With eye on China, Koizumi stresses importance of rules-based order
Defense Minister Shinjiro Koizumi speaks at the Munich Security Conference in Munich on Friday. Defense Minister Shinjiro Koizumi reiterated the importance of the rules-based global order during a speech at the Munich Security Conference while linking the security of the Indo-Pacific to the Euro-Atlantic, as Japan keeps a nervous eye on Chinese military moves in Asia. "The very foundations that have underpinned the international order are being tested by real world actions," Koizumi said Friday "Attempts to unilaterally change the status quo by force must never be tolerated. That is why Japan does not view Ukraine as a distant European problem." Following the eruption of the war in Ukraine in February 2022, Japan began drawing a link between the two regions, with leaders repeatedly stressing that "Ukraine today could be East Asia tomorrow" -- a not-so-oblique hint at the possibility of a similar regional conflict in the Indo-Pacific, especially one involving China attacking democratic Taiwan.
DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections
Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li
Neural Information Processing Systems http://nips.cc/
Multi-labelCo-regularizationforSemi-supervised FacialActionUnitRecognition
Facial action units (AUs) recognition is essential for emotion analysis and has been widely applied in mental state analysis. Existing work on AU recognition usually requires big face dataset with accurate AU labels. However, manual AU annotation requires expertise and can be time-consuming. In this work, we propose asemi-supervised approach forAUrecognition utilizing alargenumber of web face images without AU labels and a small face dataset with AU labels inspired by the co-training methods.
Discriminative Calibration: Check Bayesian
However, SBC has drawbacks: The test statistic is somewhat ad-hoc, interactions are difficult to examine, multiple testing is a challenge, and the resulting p-value is not a divergence metric.
