Refinement of Observations under Budget Constraints in Active Learning
نویسنده
چکیده
This paper addresses a new challenge in active learning: objects are described in different levels of quality and we can obtain a better version of an object at a given cost. This setting is very useful in robotics, where computing and time resources are limited. We aim to improve and label only a few objects under a given budget in an active learning setting.
منابع مشابه
A Budgeting Model for the Safety Unit of an Under Construction Metro Station in Tehran Using a Robust Optimization
Background: The construction of metro lines is a high-risk project. Using a budget-based model for the safety units of metro construction projects can help safety managers to spend optimal budget allocation. The purpose of this study was to plan a budget model based on safety unit performance in an under construction metro station for better budget allocation using robust optimization. Methods...
متن کاملProfit maximization solid transportation problem under budget constraint using fuzzy measures
Fixed charge solid transportation problems are formulated as profit maximization problems under a budget constraint at each destination. Here item is purchased in different depots at different prices. Accordingly the item is transported to different destinations from different depots using different vehicles. Unitsare sold from different destinations to the customers at different selling prices...
متن کاملController Synthesis with Budget Constraints
We study the controller synthesis problem under budget constraints. In this problem, there is a cost associated with making an observation, and a controller can make only a limited number of observations in each round so that the total cost of the observations does not exceed a given fixed budget. The controller must ensure some ω-regular requirement subject to the budget constraint. Budget con...
متن کاملApproximate Active Learning of Nondeterministic Input Output Transition Systems
Constructing a model of a system for model-based testing, simulation, or model checking can be cumbersome for existing, third party, or legacy components. Active automata learning, a form of black-box reverse engineering, and in particular Angluin’s L algorithm, support the automatic inference of a model from a System Under Learning (SUL), through observations and tests. Most of the algorithms ...
متن کاملLearning with online constraints: shifting concepts and active learning
Many practical problems such as forecasting, real-time decision making, streaming data applications, and resource-constrained learning, can be modeled as learning with online constraints. This thesis is concerned with analyzing and designing algorithms for learning under the following online constraints: i) The algorithm has only sequential, or one-at-time, access to data. ii) The time and spac...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2010