Beam Search هي استراتيجية فك التشفير الافتراضية للعديد من مهام توليد التسلسل في NLP. مجموعة من العناصر K-Best التقريبية التي تم إرجاعها بواسطة الخوارزمية هي ملخص مفيد للتوزيع للعديد من التطبيقات؛ ومع ذلك، عادة ما تظهر المرشحين تداخلا كبيرا وقد يعطي تقديرا متحيزين للغاية للتوقعات تحت نموذجنا. يمكن معالجة هذه المشكلات من خلال استخدام استراتيجيات فك تشفير الاستوكاستك. في هذا العمل، نقترح طريقة جديدة لتحويل البحث الشعاع في عملية عموقة: البحث الشرطي Poisson Stochastic Search. بدلا من اتخاذ تعظيم المجموعة في كل تكرار، ونحن نعمل عينة من المرشحين k دون استبدال وفقا لتصميم أخذ العينات poisson الشرطية. نعتبر ذلك بديلا أكثر طبيعية ل Kool et al. (2019) بحث شعاع ستوكاستيك (SBS). علاوة على ذلك، نوضح كيف يمكن استخدام العينات التي تم إنشاؤها تحت تصميم CPSBS لبناء مقدرات متسقة وعينة مجموعات متنوعة من نماذج التسلسل. في تجاربنا، نلاحظ CPSBS تنتج التباين المنخفض ومقدرات أكثر كفاءة من SBS، حتى إظهار التحسينات في إعدادات Enterpy عالية.
Beam search is the default decoding strategy for many sequence generation tasks in NLP. The set of approximate K-best items returned by the algorithm is a useful summary of the distribution for many applications; however, the candidates typically exhibit high overlap and may give a highly biased estimate for expectations under our model. These problems can be addressed by instead using stochastic decoding strategies. In this work, we propose a new method for turning beam search into a stochastic process: Conditional Poisson stochastic beam search. Rather than taking the maximizing set at each iteration, we sample K candidates without replacement according to the conditional Poisson sampling design. We view this as a more natural alternative to Kool et al. (2019)'s stochastic beam search (SBS). Furthermore, we show how samples generated under the CPSBS design can be used to build consistent estimators and sample diverse sets from sequence models. In our experiments, we observe CPSBS produces lower variance and more efficient estimators than SBS, even showing improvements in high entropy settings.
References used
https://aclanthology.org/
The implementation of the most important next stages of the
verdict after the owner of the right to obtain unread become
final judgment in favor of the right and protect it he must
implement this provision to reach the right word and deed
And imp
Symptoms of the progress of the civil case are events or facts that the lawsuit is exposed to in terms of form and before entering into the matter, and which lead to the suspension or temporary suspension of the proceeding in the case. There are cert
The purpose of this research is to study and create a stochastic mathematical model
based on a renewable energy source (wind).
The question of finding optimal values for the variables of the mathematical model
subject to stochastic conditions is one of the random mathematical problems, which require
special stochastic methods to solve in the general case.
We present in this article a game of chance (Saint Petersburg Paradox) and
generalize it on a probability space as an example of a previsible (predictable) process,
from which we get a discrete stochastic integration (DSI). Then we define a marting
Conditional Random Field (CRF) based neural models are among the most performant methods for solving sequence labeling problems. Despite its great success, CRF has the shortcoming of occasionally generating illegal sequences of tags, e.g. sequences c