The Frontier of Intractability for EFX with Two Agents

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Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

Compute memories are memory arrays augmented with dedicated logic to support arithmetic. They support the efficient execution of data-centric computing patterns, such as those characterizing Artificial Intelligence (AI) algorithms. These architectures can ...

Discrete sizing and topology optimization of truss structures subject to stress and displacement constraints has been formulated as a Mixed-Integer Linear Programming (MILP) problem. The computation time to solve a MILP problem to global optimality via a b ...

In this paper, we tackle the problem of static 3D cloth draping on virtual human bodies. We introduce a two-stream deep network model that produces a visually plausible draping of a template cloth on virtual 3D bodies by extracting features from both the b ...

In-band full-duplex systems allow for more efficient use of temporal and spectral resources by transmitting and receiving information at the same time and on the same frequency. However, this creates a strong self-interference signal at the receiver, makin ...

In the first part of this two-part paper we show that the branch-flow convexification of the OPF problem is not exact and that the ADMM-based decomposition of the OPF fails to converge in specific scenarios. Therefore, there is a need to develop algorithms ...

The Learning Parity with Noise problem (LPN) is appealing in cryptography as it is considered to remain hard in the post-quantum world. It is also a good candidate for lightweight devices due to its simplicity. In this paper we provide a comprehensive anal ...

The Frontier of Intractability for EFX with Two Agents

Chattez avec Graph Search

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Overflow-free Compute Memories for Edge AI Acceleration

MILP-based discrete sizing and topology optimization of truss structures: new formulation and benchmarking

GarNet++: Improving Fast and Accurate Static 3D Cloth Draping by Curvature Loss

Advanced Machine Learning Techniques for Self-Interference Cancellation in Full-Duplex Radios

Adaptive balancing of gradient and update computation times using global geometry and approximate subproblems

AC OPF in radial distribution networks – Part II: An augmented Lagrangian-based OPF algorithm, distributable via primal decomposition

On solving LPN using BKW and variants Implementation and Analysis