Analyzed convergence of decentralized gradient descent with fixed step size, achieving O(1/k) rate and linear convergence under strong convexity.

Kun Yuan, Qing Ling, Wotao Yin

Distributed reactive power control via ADMM reduces power losses and maintains voltage stability in photovoltaic-integrated grids.

Petr Šulc, Scott Backhaus, Michael Chertkov

Proposes a game-theoretic double auction mechanism improving storage unit utility by 130.2%.

Yunpeng Wang, Walid Saad, Zhu Han et al.

Proposed an efficient training method for NADE models, enhancing density estimation performance.

Benigno Uria, Iain Murray, Hugo Larochelle

DeCAF features extracted from ImageNet-trained CNN outperform traditional features on multiple vision tasks, achieving over 20% accuracy improvements.

Jeff Donahue, Yangqing Jia, Oriol Vinyals et al.

Turney’s dual-space model unifies analogy and composition through domain/function cosine similarities; the supplied text omits numerical scores.

Peter D. Turney

Survey on data-driven grasp synthesis methods, categorized by known, familiar, and unknown objects.

Jeannette Bohg, Antonio Morales, Tamim Asfour et al.

Four gradient estimators for stochastic binary neurons enable efficient conditional computation and sparsity in deep networks.

Yoshua Bengio, Nicholas Léonard, Aaron Courville

Using spinor helicity and BCFW recursion, the paper simplifies multi-particle scattering amplitudes, improving computational efficiency.

Henriette Elvang, Yu-tin Huang

Introduces a Linearized Phrase Structure model to improve semantic orientation detection in financial texts.

Pekka Malo, Ankur Sinha, Pyry Takala et al.

Introduces Exp3-DOM algorithm leveraging dominating sets to bound regret in directed, dynamic observation graphs (under 30 words)

Noga Alon, Nicolò Cesa-Bianchi, Claudio Gentile et al.

The report summarizes three ICML 2013 challenges: black box learning, facial expression recognition, and multimodal learning.

Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier et al.

SLIM combines 0–1 loss, L0 sparsity, and integer constraints to produce accurate, hand-computable scoring systems.

Berk Ustun, Stefano Tracà, Cynthia Rudin

Proposes a loss-function-based Bayesian updating framework, suitable for models with incomplete information or parameters not directly linked to densities.

Pier Giovanni Bissiri, Chris Holmes, Stephen Walker

FGVC-Aircraft dataset includes 100 aircraft models, offering a benchmark for fine-grained visual classification.

Subhransu Maji, Esa Rahtu, Juho Kannala et al.

Modern proof of Hanson-Wright inequality for sub-gaussian quadratic forms, deriving concentration bounds for high-dimensional vectors and matrices.

Mark Rudelson, Roman Vershynin

Proposes BOLD and QPM-D algorithms for online learning with delayed feedback; theoretical bounds show multiplicative regret in adversarial and additive in stochastic settings.

Pooria Joulani, András György, Csaba Szepesvári

Proposed graph-cluster randomization method significantly reduces estimator variance under network interference.

Johan Ugander, Brian Karrer, Lars Backstrom et al.

Using survival theory to model information propagation, proposing additive and multiplicative risk models for efficient network inference.

Manuel Gomez Rodriguez, Jure Leskovec, Bernhard Schoelkopf

Proposes GP-UCB-PE, combining UCB and pure exploration for parallel Gaussian process optimization, with bounds outperforming sequential methods.

Emile Contal, David Buffoni, Alexandre Robicquet et al.