Zobrazeno 1 - 10
of 76
pro vyhledávání: '"Ramamurthy, Arun"'
Autor:
Chen, Wei, Ramamurthy, Arun
In aerodynamic shape optimization, the convergence and computational cost are greatly affected by the representation capacity and compactness of the design space. Previous research has demonstrated that using a deep generative model to parameterize t
Externí odkaz:
http://arxiv.org/abs/2101.02744
Existing approaches for open-domain question answering (QA) are typically designed for questions that require either single-hop or multi-hop reasoning, which make strong assumptions of the complexity of questions to be answered. Also, multi-step docu
Externí odkaz:
http://arxiv.org/abs/2009.07465
Designing resource-efficient Deep Neural Networks (DNNs) is critical to deploy deep learning solutions over edge platforms due to diverse performance, power, and memory budgets. Unfortunately, it is often the case a well-trained ML model does not fit
Externí odkaz:
http://arxiv.org/abs/2006.03969
To efficiently run DNNs on the edge/cloud, many new DNN inference accelerators are being designed and deployed frequently. To enhance the resource efficiency of DNNs, model quantization is a widely-used approach. However, different accelerator/HW has
Externí odkaz:
http://arxiv.org/abs/2006.03968
Recent studies on open-domain question answering have achieved prominent performance improvement using pre-trained language models such as BERT. State-of-the-art approaches typically follow the "retrieve and read" pipeline and employ BERT-based reran
Externí odkaz:
http://arxiv.org/abs/2002.12591
Markov Logic Networks (MLNs), which elegantly combine logic rules and probabilistic graphical models, can be used to address many knowledge graph problems. However, inference in MLN is computationally intensive, making the industrial-scale applicatio
Externí odkaz:
http://arxiv.org/abs/2001.11850
Effectively combining logic reasoning and probabilistic inference has been a long-standing goal of machine learning: the former has the ability to generalize with small training data, while the latter provides a principled framework for dealing with
Externí odkaz:
http://arxiv.org/abs/1906.02111
Autor:
Ramamurthy, Arun, Sathya, Vanlin, Ghosh, Shrestha, Franklin, Antony, Tamma, Bheemarjuna Reddy
The recent developments in full duplex (FD) communication promise doubling the capacity of cellular networks using self interference cancellation (SIC) techniques. FD small cells with device-to-device (D2D) communication links could achieve the expec
Externí odkaz:
http://arxiv.org/abs/1606.07198
Autor:
Ramamurthy, Arun
An important class of compute accelerators are graphics processing units (GPUs). Popular programming models for non-graphics computation on GPUs, such as CUDA and OpenCL, provide an abstraction of many parallel scalar threads. Contemporary GPU hardwa
Externí odkaz:
http://hdl.handle.net/2429/37732
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