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20102026
most citedLearning Latent Dynamics for Planning from Pixels

339 citations

Showing 2018Show all

37 papers · 1 filter

cs.CV2018

LoANs: Weakly Supervised Object Detection with Localizer Assessor Networks

Christian Bartz, Haojin Yang, Joseph Bethge +1

Recently, deep neural networks have achieved remarkable performance on the task of object detection and recognition. The reason for this success is mainly grounded in the availabil…

cs.DS2018★ 61 cited

Pareto Optimization for Subset Selection with Dynamic Cost Constraints

Vahid Roostapour, Aneta Neumann, Frank Neumann +1

We consider the subset selection problem for function with constraint bound that changes over time. Within the area of submodular optimization, various greedy approaches ar…

cs.LG2018★ 339 cited

Learning Latent Dynamics for Planning from Pixels

Danijar Hafner, Timothy Lillicrap, Ian Fischer +4

Planning has been very successful for control tasks with known environment dynamics. To leverage planning in unknown environments, the agent needs to learn the dynamics from intera…

cs.CY2018★ 21 cited

Effects of Automated Interventions in Programming Assignments: Evidence from a Field Experiment

Ralf Teusner, Thomas Hille, Thomas Staubitz

A typical problem in MOOCs is the missing opportunity for course conductors to individually support students in overcoming their problems and misconceptions. This paper presents th…

cs.HC2018★ 6 cited

Taking Informed Action on Student Activity in MOOCs

Ralf Teusner, Kai-Adrian Rollmann, Jan Renz

This paper presents a novel approach to understand specific student behavior in MOOCs. Instructors currently perceive participants only as one homogeneous group. In order to improv…

cs.SE2018★ 8 cited

Aspects on Finding the Optimal Practical Programming Exercise for MOOCs

Ralf Teusner, Thomas Hille, Christiane Hagedorn

Massive Open Online Courses (MOOCs) focus on manifold subjects, ranging from social sciences over languages to technical skills, and use different means to train the respective ski…