Search
Skip to Search Results- 19Jagersand, Martin (Computing Science)
- 15Szepesvari, Csaba (Computing Science)
- 4Schuurmans, Dale (Computing Science)
- 3Cobzas, Dana (Computing Science)
- 1Andras Gyorgy (Imperial College London, U.K.)
- 1Bowling, Michael (Computing Science)
- 2Joulani, Pooria
- 1Abbasi-Yadkori, Yasin
- 1Afkanpour, Arash
- 1Ahmad, Junaid
- 1Aslan,Ozlem
- 1Balazs, Gabor
- 7Robotics
- 4Online Learning
- 4Reinforcement Learning
- 3Learning theory
- 3Machine Learning
- 2Computer Vision
-
A NEW VISUAL TRACKING ALGORITHM BASED ON TEMPLATE REGISTRATION FOR ACCURATE OBJECT TRACKING
DownloadSpring 2016
Visual tracking serves an important role in a wide variety of applications like video surveillance, robotic manipulation and augmented reality. The goal of tracking in the last two cases here is to efficiently and accurately locate the object in each frame of an image sequence/stream, with the...
-
Fall 2013
Medical image registration and segmentation are challenging because, medical images are generally corrupted by noise, image artifacts and the various anatomical regions of interest in medical images often do not have distinct sharp boundaries. However, these anatomical regions frequently...
-
Spring 2023
Choosing an appropriate action representation is an integral part of solving robotic manipulation problems. Published approaches include latent action models, which train context-conditioned neural networks to map lowdimensional latent actions to high-dimensional actuation commands. Such models...
-
Spring 2023
Wheelchair-mounted robotic manipulators have the potential to help the elderly and individuals living with disabilities carry out their activities of daily living independently. While robotics researchers focus on assistive tasks from the perspective of various control schemes and motion types, ...
-
Spring 2017
Optimizing an objective function over convex sets is a key problem in many different machine learning models. One of the various kinds of well studied objective functions is the convex function, where any local minimum must be the global mini- mum over the domain. To find the optimal point that...
-
Computer Vision-Based Motion Control and State Estimation for Unmanned Aerial Vehicles (UAVs)
DownloadSpring 2018
To achieve a fully autonomous unmanned aerial vehicle (UAV) the vehicle needs a high level of self awareness. At a minimum it needs to know where it is and where it wants to go. Computer vision (CV) is a logical solution to this problem. However, using CV to solve motion control problems for UAVs...
-
Spring 2017
Most machine learning problems can be posed as solving a mathematical program that describes the structure of the prediction problem, usually expressed in terms of carefully chosen losses and regularizers. However, many machine learning problems yield mathematical programs that are not convex in...
-
Fall 2016
This thesis explores theoretical, computational, and practical aspects of convex (shape-constrained) regression, providing new excess risk upper bounds, a comparison of convex regression techniques with theoretical guarantee, a novel heuristic training algorithm for max-affine representations,...
-
Decision Frequency Adaptation in Reinforcement Learning Using Continuous Options with Open-Loop Policies
DownloadFall 2023
In classic reinforcement learning(RL) for continuous control, agents make decisions at discrete and fixed time intervals. The duration between decisions becomes a crucial hyperparameter. Setting it too short may increase the problem’s difficulty by requiring the agent to make numerous decisions...
-
Fall 2023
A matroid bandit is the online version of combinatorial optimization on a matroid, in which the learner chooses $K$ actions from a set of $L$ actions that can form a matroid basis. Many real-world applications such as recommendation systems can be modeled as matroid bandits. In such learning...