Carlo Baldassi

According to our database1, Carlo Baldassi authored at least 23 papers between 2007 and 2020.

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Bibliography

2020
Predicting Interacting Protein Pairs by Coevolutionary Paralog Matching.
Proceedings of the Protein-Protein Interaction Networks, Methods and Protocols., 2020

Shaping the learning landscape in neural networks around wide flat minima.
Proc. Natl. Acad. Sci. USA, 2020

A Behavioral Characterization of the Drift Diffusion Model and Its Multialternative Extension for Choice Under Time Pressure.
Manag. Sci., 2020

Wide flat minima and optimal generalization in classifying high-dimensional Gaussian mixtures.
CoRR, 2020

Ergodic Annealing.
CoRR, 2020

Entropic gradient descent algorithms and wide flat minima.
CoRR, 2020

Multialternative Neural Decision Process.
CoRR, 2020

2019
Natural representation of composite data with replicated autoencoders.
CoRR, 2019

On the geometry of solutions and on the capacity of multi-layer neural networks with ReLU activations.
CoRR, 2019

Recombinator-k-means: Enhancing k-means++ by seeding from pools of previous runs.
CoRR, 2019

2018
Efficiency of quantum vs. classical annealing in nonconvex learning problems.
Proc. Natl. Acad. Sci. USA, 2018

2017
On the role of synaptic stochasticity in training low-precision neural networks.
CoRR, 2017

Parle: parallelizing stochastic gradient descent.
CoRR, 2017

Efficiency of quantum versus classical annealing in non-convex learning problems.
CoRR, 2017

Entropy-SGD: Biasing Gradient Descent Into Wide Valleys.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes.
Proc. Natl. Acad. Sci. USA, 2016

Unreasonable Effectiveness of Learning Neural Nets: Accessible States and Robust Ensembles.
CoRR, 2016

2015
Binary Synapse Circuitry for High Efficiency Learning Algorithm Using Generalized Boundary Condition Memristor Models.
Proceedings of the Advances in Neural Networks: Computational and Theoretical Issues, 2015

A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks.
PLoS Comput. Biol., 2015

A Max-Sum algorithm for training discrete neural networks.
CoRR, 2015

2014
Sharing Information to Reconstruct Patient-Specific Pathways in Heterogeneous Diseases.
Proceedings of the Biocomputing 2014: Proceedings of the Pacific Symposium, 2014

2013
Shape Similarity, Better than Semantic Membership, Accounts for the Structure of Visual Object Representations in a Population of Monkey Inferotemporal Neurons.
PLoS Comput. Biol., 2013

2007
Efficient supervised learning in networks with binary synapses.
Proc. Natl. Acad. Sci. USA, 2007


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