اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدProceedings of the 4th annual Underrepresented Students in Topology and Algebra Research Symposium (USTARS 2014)
47
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
This volume represents the proceedings of the 4th annual meetings of the Underrepresented Students in Topology and Algebra Research Symposium (USTARS 2014), held on 11-13 April 2014 in Berkeley, California.
قيم البحث
اقرأ أيضاً
To any toric ideal $I_A$, encoded by an integer matrix $A$, we associate a matroid structure called {em the bouquet graph} of $A$ and introduce another toric ideal called {em the bouquet ideal} of $A$. We show how these objects capture the essential
combinatorial and algebraic information about $I_A$. Passing from the toric ideal to its bouquet ideal reveals a structure that allows us to classify several cases. For example, on the one end of the spectrum, there are ideals that we call {em stable}, for which bouquets capture the complexity of various generating sets as well as the minimal free resolution. On the other end of the spectrum lie toric ideals whose various bases (e.g., minimal generating sets, Grobner, Graver bases) coincide. Apart from allowing for classification-type results, bouquets provide a new way to construct families of examples of toric ideals with various interesting properties, such as robustness, genericity, and unimodularity. The new bouquet framework can be used to provide a characterization of toric ideals whose Graver basis, the universal Grobner basis, any reduced Grobner basis and any minimal generating set coincide.
Report of the experimental activities in Hall A at Thomas Jefferson National Accelerator Facility during 2013.
Proceedings of ISMD08
The Artificial Intelligence (AI) for Human-Robot Interaction (HRI) Symposium has been a successful venue of discussion and collaboration since 2014. In that time, the related topic of trust in robotics has been rapidly growing, with major research ef
forts at universities and laboratories across the world. Indeed, many of the past participants in AI-HRI have been or are now involved with research into trust in HRI. While trust has no consensus definition, it is regularly associated with predictability, reliability, inciting confidence, and meeting expectations. Furthermore, it is generally believed that trust is crucial for adoption of both AI and robotics, particularly when transitioning technologies from the lab to industrial, social, and consumer applications. However, how does trust apply to the specific situations we encounter in the AI-HRI sphere? Is the notion of trust in AI the same as that in HRI? We see a growing need for research that lives directly at the intersection of AI and HRI that is serviced by this symposium. Over the course of the two-day meeting, we propose to create a collaborative forum for discussion of current efforts in trust for AI-HRI, with a sub-session focused on the related topic of explainable AI (XAI) for HRI.
This is the Proceedings of NIPS 2017 Symposium on Interpretable Machine Learning, held in Long Beach, California, USA on December 7, 2017
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
