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Found 8 papers, 3 papers with code
Unsupervised Multi-View Post-OCR Error Correction With Language Models
We investigate post-OCR correction in a setting where we have access to different OCR views of the same document.
Cross-Geography Generalization of Machine Learning Methods for Classification of Flooded Regions in Aerial Images
This work proposes two approaches for identifying flooded regions in UAV aerial images.
Combining Reinforcement Learning with Model Predictive Control for On-Ramp Merging
We consider the problem of designing an algorithm to allow a car to autonomously merge on to a highway from an on-ramp.
The Mean-Squared Error of Double Q-Learning
In this paper, we establish a theoretical comparison between the asymptotic mean-squared error of Double Q-learning and Q-learning.
Mixed Logit Models and Network Formation
We also illustrate how to use the RC model to accurately study network formation using both synthetic and real-world networks.
Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement Learning
We study two time-scale linear stochastic approximation algorithms, which can be used to model well-known reinforcement learning algorithms such as GTD, GTD2, and TDC.
Almost Boltzmann Exploration
In this paper, we show that a simple modification to Boltzmann exploration, motivated by a variation of the standard doubling trick, achieves $O(K\log^{1+\alpha} T)$ regret for a stochastic MAB problem with $K$ arms, where $\alpha>0$ is a parameter of the algorithm.
Multimodal Content Analysis for Effective Advertisements on YouTube
The objective of this work is then to measure the effectiveness of an advertisement, and to recommend a useful set of features to advertisement designers to make it more successful and approachable to users.
