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Methodology
← Optimization & Theory
Machine Learning
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Optimization & Theory
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Neural Network Optimization
3648 directly classified papers
Papers per year
2001: 1
2003: 1
2005: 2
2006: 3
2007: 6
2008: 1
2009: 7
2010: 5
2011: 7
2012: 9
2013: 17
2014: 18
2015: 40
2016: 76
2017: 113
2018: 214
2019: 324
2020: 414
2021: 489
2022: 445
2023: 524
2024: 469
2025: 386
2026: 77
Papers
Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation
AISTATS 2020
Automatic Differentiation of Some First-Order Methods in Parametric Optimization
AISTATS 2020
Adaptive Gradient Descent without Descent
ICML 2020
Target Propagation in Recurrent Neural Networks
JMLR 2020
CP-NAS: Child-Parent Neural Architecture Search for 1-bit CNNs
IJCAI 2020
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search
IJCAI 2020
Overflow Aware Quantization: Accelerating Neural Network Inference by Low-bit Multiply-Accumulate Operations
IJCAI 2020
LSGCN: Long Short-Term Traffic Prediction with Graph Convolutional Networks
IJCAI 2020
Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling
IJCAI 2020
NSGA-Net: Neural Architecture Search using Multi-Objective Genetic Algorithm (Extended Abstract)
IJCAI 2020
Visual Speech In Real Noisy Environments (VISION): A Novel Benchmark Dataset and Deep Learning-Based Baseline System
INTERSPEECH 2020
ForceReader: a BERT-based Interactive Machine Reading Comprehension Model with Attention Separation
COLING 2020
ERMI at PARSEME Shared Task 2020: Embedding-Rich Multiword Expression Identification
COLING 2020
Ferryman at SemEval-2020 Task 3: Bert with TFIDF-Weighting for Predicting the Effect of Context in Word Similarity
COLING 2020
Evolved Speech-Transformer: Applying Neural Architecture Search to End-to-End Automatic Speech Recognition
INTERSPEECH 2020
Acoustic-to-Articulatory Inversion with Deep Autoregressive Articulatory-WaveNet
INTERSPEECH 2020
LVCSR with Transformer Language Models
INTERSPEECH 2020
Finite Regret and Cycles with Fixed Step-Size via Alternating Gradient Descent-Ascent
COLT 2020
Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process
COLT 2020
Gradient descent follows the regularization path for general losses
COLT 2020
Time-Aware Transformer-based Network for Clinical Notes Series Prediction
MLHC 2020
Functional Gradient Boosting for Learning Residual-like Networks with Statistical Guarantees
AISTATS 2020
iCompass at SemEval-2020 Task 12: From a Syntax-ignorant N-gram Embeddings Model to a Deep Bidirectional Language Model
COLING 2020
UoB at SemEval-2020 Task 12: Boosting BERT with Corpus Level Information
COLING 2020
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss
COLT 2020
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