Efficient Online Learning for Mapping Kernels on Linguistic Structures

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Kernels on Linguistic Structures for Answer Extraction

Natural Language Processing (NLP) for Information Retrieval has always been an interesting and challenging research area. Despite the high expectations, most of the results indicate that successfully using NLP is very complex. In this paper, we show how Support Vector Machines along with kernel functions can effectively represent syntax and semantics. Our experiments on question/answer classifi...

متن کامل

Online Learning for Structural Kernels

While online learning techniques have existed since Rosenblatt’s introduction of the Perceptron in 1957, there has been a renewed interest lately due to the need for efficient classification algorithms. Additionally, kernel techniques have allowed online learning to be extended to problems whose classes are not linearly separable in their native space. Online algorithms typically result in poor...

متن کامل

Decentralized Online Learning with Kernels

We consider multi-agent stochastic optimization problems over reproducing kernel Hilbert spaces (RKHS). In this setting, a network of interconnected agents aims to learn decision functions, i.e., nonlinear statistical models, that are optimal in terms of a global convex functional that aggregates data across the network, with only access to locally and sequentially observed samples. We propose ...

متن کامل

Online Imbalanced Learning with Kernels

Imbalanced learning, or learning from imbalanced data, is a challenging problem in both academy and industry. Nowadays, the streaming imbalanced data become popular and trigger the volume, velocity, and variety issues of learning from these data. To tackle these issues, online learning algorithms are proposed to learn a linear classifier via maximizing the AUC score. However, the developed line...

متن کامل

implicit Online Learning with Kernels

We present two new algorithms for online learning in reproducing kernel Hilbert spaces. Our first algorithm, ILK (implicit online learning with kernels), employs a new, implicit update technique that can be applied to a wide variety of convex loss functions. We then introduce a bounded memory version, SILK (sparse ILK), that maintains a compact representation of the predictor without compromisi...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Proceedings of the AAAI Conference on Artificial Intelligence

سال: 2019

ISSN: 2374-3468,2159-5399

DOI: 10.1609/aaai.v33i01.33013421