Optimizing Nondecomposable Loss Functions in Structured Prediction

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود 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

Optimizing Complex Loss Functions in Structured Prediction

In this paper we develop an algorithm for structured prediction that optimizes against complex performance measures, those which are a function of false positive and false negative counts. The approach can be directly applied to performance measures such as Fβ score (natural language processing), intersection over union (image segmentation), Precision/Recall at k (search engines) and ROC area (...

متن کامل

Training Structured Prediction Models with Extrinsic Loss Functions

We present an online learning algorithm for training structured prediction models with extrinsic loss functions. This allows us to extend a standard supervised learning objective with additional loss-functions, either based on intrinsic or taskspecific extrinsic measures of quality. We present experiments with sequence models on part-of-speech tagging and named entity recognition tasks, and wit...

متن کامل

Optimizing functions of coagulants in treatment of wastewater from metalworking fluids: Prediction by RSM method

Background: Coagulation is a treatment procedure for metalworking fluids (MWFs). This study aimed to optimize coagulation using four coagulants and compare the results. Methods: In this research, the outputs of a coagulation procedure in chemical oxygen demand (COD) removal, turbidity, and the release of oil were investigated using four coagulants, ferric chloride (FeCl3), ferric sulfate (Fe2(...

متن کامل

Loss Functions for Multiset Prediction

We study the problem of multiset prediction. The goal of multiset prediction is to train a predictor that maps an input to a multiset consisting of multiple items. Unlike existing problems in supervised learning, such as classification, ranking and sequence generation, there is no known order among items in a target multiset, and each item in the multiset may appear more than once, making this ...

متن کامل

Direct Loss Minimization for Structured Prediction

In discriminative machine learning one is interested in training a system to optimize a certain desired measure of performance, or loss. In binary classification one typically tries to minimizes the error rate. But in structured prediction each task often has its own measure of performance such as the BLEU score in machine translation or the intersection-over-union score in PASCAL segmentation....

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: IEEE Transactions on Pattern Analysis and Machine Intelligence

سال: 2013

ISSN: 0162-8828,2160-9292

DOI: 10.1109/tpami.2012.168