Efficient deep learning: A survey on making deep learning models smaller, faster, and better
G Menghani - ACM Computing Surveys, 2023 - dl.acm.org
Deep learning has revolutionized the fields of computer vision, natural language
understanding, speech recognition, information retrieval, and more. However, with the …
understanding, speech recognition, information retrieval, and more. However, with the …
Hyper-parameter optimization: A review of algorithms and applications
T Yu, H Zhu - arxiv preprint arxiv:2003.05689, 2020 - arxiv.org
Since deep neural networks were developed, they have made huge contributions to
everyday lives. Machine learning provides more rational advice than humans are capable of …
everyday lives. Machine learning provides more rational advice than humans are capable of …
Promptbreeder: Self-referential self-improvement via prompt evolution
Popular prompt strategies like Chain-of-Thought Prompting can dramatically improve the
reasoning abilities of Large Language Models (LLMs) in various domains. However, such …
reasoning abilities of Large Language Models (LLMs) in various domains. However, such …
Aasist: Audio anti-spoofing using integrated spectro-temporal graph attention networks
Artefacts that differentiate spoofed from bona-fide utterances can reside in specific temporal
or spectral intervals. Their reliable detection usually depends upon computationally …
or spectral intervals. Their reliable detection usually depends upon computationally …
End-to-end speech recognition: A survey
In the last decade of automatic speech recognition (ASR) research, the introduction of deep
learning has brought considerable reductions in word error rate of more than 50% relative …
learning has brought considerable reductions in word error rate of more than 50% relative …
Agent57: Outperforming the atari human benchmark
Atari games have been a long-standing benchmark in the reinforcement learning (RL)
community for the past decade. This benchmark was proposed to test general competency …
community for the past decade. This benchmark was proposed to test general competency …
A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and …
Ensembles, especially ensembles of decision trees, are one of the most popular and
successful techniques in machine learning. Recently, the number of ensemble-based …
successful techniques in machine learning. Recently, the number of ensemble-based …
Streamflow prediction using an integrated methodology based on convolutional neural network and long short-term memory networks
Streamflow (Q flow) prediction is one of the essential steps for the reliable and robust water
resources planning and management. It is highly vital for hydropower operation, agricultural …
resources planning and management. It is highly vital for hydropower operation, agricultural …
Emergent tool use from multi-agent autocurricula
Through multi-agent competition, the simple objective of hide-and-seek, and standard
reinforcement learning algorithms at scale, we find that agents create a self-supervised …
reinforcement learning algorithms at scale, we find that agents create a self-supervised …
Collaborating with humans without human data
Collaborating with humans requires rapidly adapting to their individual strengths,
weaknesses, and preferences. Unfortunately, most standard multi-agent reinforcement …
weaknesses, and preferences. Unfortunately, most standard multi-agent reinforcement …