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Near-Optimally Teaching the Crowd to Classify 
Related publications (34)
Applications of Derandomization Theory in Coding
Mahdi Cheraghchi Bashi Astaneh
Randomized techniques play a fundamental role in theoretical computer science and discrete mathematics, in particular for the design of efficient algorithms and construction of combinatorial objects. The basic goal in derandomization theory is to eliminate ...
EPFL2010Pre-Synthesis Optimization of Arithmetic Circuits
The efficient synthesis of circuits is a well-studied problem. Due to the NP-hardness of the problem, no optimal algorithm has been presented so far. However, the heuristics presented by several researchers in the past, which are also adopted by commercial ...
EPFL2010M-DPOP: Faithful distributed implementation of efficient social choice problems
Boi Faltings, Adrian Petcu, David C. Parkes
In the efficient social choice problem, the goal is to assign values, subject to side constraints, to a set of variables to maximize the total utility across a population of agents, where each agent has private information about its utility function. In th ...
2008World-set Decompositions: Expressiveness and Efficient Algorithms
Uncertain information is commonplace in real-world data management scenarios. The ability to represent large sets of possible instances (worlds) while supporting efficient storage and processing is an important challenge in this context. The recent formali ...
2007Packet Selection and Scheduling for Multipath Video Streaming
This paper addresses the problem of choosing the best streaming policy for distortion optimal multipath video delivery, under delay constraints. The streaming policy consists in a joint selection of the video packets to be transmitted, as well as their sen ...
2007MOTIF: AN EFFICIENT ALGORITHM FOR LEARNING TRANSLATION INVARIANT DICTIONARIES
Pierre Vandergheynst, Rémi Gribonval, Philippe Jost
The performances of approximation using redundant expansions rely on having dictionaries adapted to the signals. In natural high-dimensional data, the statistical dependencies are, most of the time, not obvious. Learning fundamental patterns is an alternat ...
2006Distortion Optimized Multipath Video Streaming
This paper addresses the problem of choosing the best streaming policy for distortion optimal multipath video delivery, under delay constraints. The streaming policy consists in a joint selection of the video packets to be transmitted, as well as their sen ...
2004Packet Selection and Scheduling for Multipath Video Streaming
This paper addresses the problem of choosing the best streaming policy for distortion optimal multipath video delivery, under delay constraints. The streaming policy consists in a joint selection of the video packets to be transmitted, as well as their sen ...
2004Using the Breakout Algorithm to Identify Hard and Unsolvable Subproblems
Boi Faltings, Carlos Eisenberg
Local search algorithms have been very successful for solving constraint satisfaction problems (CSP). However, a major weakness has been that local search is unable to detect unsolvability and is thus not suitable for highly constrained or overconstrained ...
Swiss Federal Institute of Technology (EPFL)2003Constraint-Based Mining of Sequential Patterns over Datasets with Consecutive Repetitions
onstraint-based mining of sequential patterns is an active research area motivated by many application domains. In practice, the real sequence datasets can present consecutive repetitions of symbols (e.g., DNA sequences, discretized stock market data) that ...
Springer2003