Information-based recognition: TED talks and the institutional fabric of valuable innovation

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Collaborative learning algorithms, such as distributed SGD (or D-SGD), are prone to faulty machines that may deviate from their prescribed algorithm because of software or hardware bugs, poisoned data or malicious behaviors. While many solutions have been ...

This work addresses the problem of sharing partial information within social learning strategies. In social learning, agents solve a distributed multiple hypothesis testing problem by performing two operations at each instant: first, agents incorporate inf ...

Information is the resolution of uncertainty and manifests itself as patterns. Although complex, most observable phenomena are not random and instead are associated with deterministic, chaotic systems. The underlying patterns and symmetries expressed from ...

Strategic information is valuable either by remaining private (for instance if it is sensitive) or, on the other hand, by being used publicly to increase some utility. These two objectives are antagonistic and leaking this information by taking full advant ...

The heterogeneity of today's Web sources requires information retrieval (IR) systems to handle multi-modal queries. Such queries define a user's information needs by different data modalities, such as keywords, hashtags, user profiles, and other media. Rec ...

The transmission overload after a disturbance poses significant security risk to the power system. Once it happens, an efficient remedial action must be taken to relieve the line overloads as quickly as possible. The line overload mitigation problem become ...

Universal inference enables the construction of confidence intervals and tests without regularity conditions by splitting the data into two parts and appealing to Markov's inequality. Previous investigations have shown that the cost of this generality is a ...

Information-based recognition: TED talks and the institutional fabric of valuable innovation

Chat with Graph Search

Robust Collaborative Learning with Linear Gradient Overhead

Partial Information Sharing Over Social Learning Networks

Measurement in the Age of Information

Utility/privacy trade-off as regularized optimal transport

Efficient and Effective Multi-Modal Queries Through Heterogeneous Network Embedding

Distributed Scheme for Line Overload Mitigation With Linearized AC Power Flow

A note on universal inference