PulseAugur
EN
LIVE 05:13:56
ENTITY Maximum Mean Discrepancy (MMD)

Maximum Mean Discrepancy (MMD)

PulseAugur coverage of Maximum Mean Discrepancy (MMD) — every cluster mentioning Maximum Mean Discrepancy (MMD) across labs, papers, and developer communities, ranked by signal.

Show in brief
Total · 30d
5
5 over 90d
Releases · 30d
0
0 over 90d
Papers · 30d
5
5 over 90d
TIER MIX · 90D
TOPICS
SENTIMENT · 30D

2 day(s) with sentiment data

RECENT · PAGE 1/1 · 5 TOTAL
  1. RESEARCH · CL_115283 ·

    New DC programming method optimizes functionals in Wasserstein space · 2 sources tracked

    Researchers have developed a new method for optimizing non-convex functionals in Wasserstein space by adapting the Difference-of-Convex (DC) programming approach. This technique, applied to functionals like Maximum Mean…

  2. RESEARCH · CL_68357 ·

    New research reveals AI model extraction defenses are vulnerable

    Two new research papers highlight vulnerabilities in current defenses against AI model extraction attacks. One paper proposes a simple yet effective detector that analyzes traffic window distributions to identify deviat…

  3. RESEARCH · CL_41793 ·

    New MoE frameworks enhance time series forecasting efficiency and accuracy

    Researchers have developed new Mixture-of-Experts (MoE) frameworks for time series forecasting that aim to improve efficiency and accuracy. AME-TS uses structure-guided routing to align expert specialization with tempor…

  4. RESEARCH · CL_30610 ·

    New transport filtering method improves nonlinear, non-Gaussian approximations

    Researchers have developed a new likelihood-free transport filtering method that leverages couplings between state and observation variables. This approach reformulates the filtering analysis step as a minimization of t…

  5. RESEARCH · CL_25821 ·

    New CP-MMD method unifies kernel selection for statistical tests

    Researchers have introduced a new statistical method called Complexity-Penalized MMD (CP-MMD) to improve the accuracy of two-sample tests. This approach treats kernel selection as a model selection problem, allowing for…