Brando Miranda

According to our database1, Brando Miranda authored at least 18 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
ZIP-FIT: Embedding-Free Data Selection via Compression-Based Alignment.
CoRR, 2024

Pantograph: A Machine-to-Machine Interaction Interface for Advanced Theorem Proving, High Level Reasoning, and Data Extraction in Lean 4.
CoRR, 2024

When Do Universal Image Jailbreaks Transfer Between Vision-Language Models?
CoRR, 2024

Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive?
CoRR, 2024

An Evaluation Benchmark for Autoformalization in Lean4.
Proceedings of the Second Tiny Papers Track at ICLR 2024, 2024

A Systematic Study of the Role of Data Quality and Alignment for Fine-tuning LLMs for Enhanced Autoformalization.
Proceedings of the Second Tiny Papers Track at ICLR 2024, 2024

2023
Is Pre-training Truly Better Than Meta-Learning?
CoRR, 2023

Beyond Scale: the Diversity Coefficient as a Data Quality Metric Demonstrates LLMs are Pre-trained on Formally Diverse Data.
CoRR, 2023

Transformer Models for Type Inference in the Simply Typed Lambda Calculus: A Case Study in Deep Learning for Code.
CoRR, 2023

Are Emergent Abilities of Large Language Models a Mirage?
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
The Curse of Low Task Diversity: On the Failure of Transfer Learning to Outperform MAML and Their Empirical Equivalence.
CoRR, 2022

2021
Does MAML Only Work via Feature Re-use? A Data Centric Perspective.
CoRR, 2021

2019
Theory III: Dynamics and Generalization in Deep Networks.
CoRR, 2019

2018
A Surprising Linear Relationship Predicts Test Performance in Deep Networks.
CoRR, 2018

Theory IIIb: Generalization in Deep Networks.
CoRR, 2018

Theory of Deep Learning IIb: Optimization Properties of SGD.
CoRR, 2018

Theory of Deep Learning III: explaining the non-overfitting puzzle.
CoRR, 2018

2017
Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review.
Int. J. Autom. Comput., 2017


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