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  • Markets & Economy

Share Buybacks: A Brief Investigation

We examine whether the rise in stock buybacks has artificially propped up equity prices, suppressed market volatility, and weakened corporate balance sheets.

  • Technology

Agile Cloud Security

Two Sigma engineers explore key challenges and opportunities they encountered while systematically rebuilding cloud security processes in an automated, agile manner.

  • Data Science

Gradient Sparsification for Communication-Efficient Distributed Optimization

Modern large-scale ML applications require stochastic optimization algorithms to be implemented on distributed computational architectures. A key bottleneck is the communication overhead for exchanging information such as stochastic gradients among different workers. In this paper, to reduce the communication cost, we propose a convex optimization formulation to minimize the coding length of stochastic gradients.

  • Data Science

Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization

The authors suggest a general oracle-based framework that captures different parallel stochastic optimization settings described by a dependency graph, and derive generic lower bounds in terms of this graph, as well as lower bounds for several specific parallel optimization settings. They highlight gaps between lower and upper bounds on the oracle complexity, and cases where the “natural” algorithms are not known to be optimal.