arXiv subjects

Dinesh Garg

Publications and source records attributed to Dinesh Garg.

21 records · Page 2Linked to original sources

arXiv2014

Greedy Block Coordinate Descent (GBCD) Method for High Dimensional Quadratic Programs

High dimensional unconstrained quadratic programs (UQPs) involving massive datasets are now common in application areas such as web, social networks, etc. Unless computational resources that match up to these datasets are available, solving such problems using classical UQP methods is very difficult. This paper discusses alternatives. We first define high dimensional compliant (HDC) methods for UQPs---methods that can solve high dimensional UQPs by adapting to available computational resources. We then show that the class of block Kaczmarz and block coordinate descent (BCD) are the only existing methods that can be made HDC. As a possible answer to the question of the `best' amongst BCD methods for UQP, we propose a novel greedy BCD (GBCD) method with serial, parallel and distributed variants. Convergence rates and numerical tests confirm that the GBCD is indeed an effective method to solve high dimensional UQPs. In fact, it sometimes beats even the conjugate gradient.

math.OC↗

arXiv2012

Mechanism Design for Cost Optimal PAC Learning in the Presence of Strategic Noisy Annotators

We consider the problem of Probably Approximate Correct (PAC) learning of a binary classifier from noisy labeled examples acquired from multiple annotators (each characterized by a respective classification noise rate). First, we consider the complete information scenario, where the learner knows the noise rates of all the annotators. For this scenario, we derive sample complexity bound for the Minimum Disagreement Algorithm (MDA) on the number of labeled examples to be obtained from each annotator. Next, we consider the incomplete information scenario, where each annotator is strategic and holds the respective noise rate as a private information. For this scenario, we design a cost optimal procurement auction mechanism along the lines of Myerson's optimal auction design framework in a non-trivial manner. This mechanism satisfies incentive compatibility property, thereby facilitating the learner to elicit true noise rates of all the annotators.

cs.LG↗

arXiv2012

Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing

An exciting application of crowdsourcing is to use social networks in complex task execution. In this paper, we address the problem of a planner who needs to incentivize agents within a network in order to seek their help in executing an {\em atomic task} as well as in recruiting other agents to execute the task. We study this mechanism design problem under two natural resource optimization settings: (1) cost critical tasks, where the planner's goal is to minimize the total cost, and (2) time critical tasks, where the goal is to minimize the total time elapsed before the task is executed. We identify a set of desirable properties that should ideally be satisfied by a crowdsourcing mechanism. In particular, {\em sybil-proofness} and {\em collapse-proofness} are two complementary properties in our desiderata. We prove that no mechanism can satisfy all the desirable properties simultaneously. This leads us naturally to explore approximate versions of the critical properties. We focus our attention on approximate sybil-proofness and our exploration leads to a parametrized family of payment mechanisms which satisfy collapse-proofness. We characterize the approximate versions of the desirable properties in cost critical and time critical domain.

cs.GT↗