37 citations · 137 across the 20 of their papers we have counts for
24 papers
AxOMaP: Designing FPGA-based Approximate Arithmetic Operators using Mathematical Programming
Siva Satyendra Sahoo, Salim Ullah, Akash Kumar
With the increasing application of machine learning (ML) algorithms in embedded systems, there is a rising necessity to design low-cost computer arithmetic for these resource-const…
AxOCS: Scaling FPGA-based Approximate Operators using Configuration Supersampling
Siva Satyendra Sahoo, Salim Ullah, Soumyo Bhattacharjee +1
The rising usage of AI and ML-based processing across application domains has exacerbated the need for low-cost ML implementation, specifically for resource-constrained embedded sy…
Temporal Patience: Efficient Adaptive Deep Learning for Embedded Radar Data Processing
Max Sponner, Julius Ott, Lorenzo Servadei +3
Radar sensors offer power-efficient solutions for always-on smart devices, but processing the data streams on resource-constrained embedded platforms remains challenging. This pape…
Magnetic Proximity induced efficient charge-to-spin conversion in large area PtSe/NiFe heterostructures
Richa Mudgal, Alka Jakhar, Pankhuri Gupta +11
As a topological Dirac semimetal with controllable spin-orbit coupling and conductivity, PtSe, a transition-metal dichalcogenide, is a promising material for several applicatio…
A Large-Scale Analysis on Self-Supervised Video Representation Learning
Akash Kumar, Ashlesha Kumar, Vibhav Vineet +1
Self-supervised learning is an effective way for label-free model pre-training, especially in the video domain where labeling is expensive. Existing self-supervised works in the vi…
Ultra-low current 10 nm spin Hall nano-oscillators
Nilamani Behera, Avinash Kumar Chaurasiya, Victor H. González +6
Nano-constriction based spin Hall nano-oscillators (SHNOs) are at the forefront of spintronics research for emerging technological applications such as oscillator-based neuromorphi…
Phase noise analysis of mutually synchronized spin Hall nano-oscillators
Artem Litvinenko, Akash Kumar, Mona Rajabali +3
The reduction of phase noise in electronic systems is of utmost importance in modern communication and signal processing applications and requires an understanding of the underlyin…
Robust mutual synchronization in long spin Hall nano-oscillator chains
Akash Kumar, Himanshu Fulara, Roman Khymyn +7
Mutual synchronization of N serially connected spintronic nano-oscillators increases their coherence by a factor and their output power by . Increasing the number of mutua…
Combining Gradients and Probabilities for Heterogeneous Approximation of Neural Networks
Elias Trommer, Bernd Waschneck, Akash Kumar
This work explores the search for heterogeneous approximate multiplier configurations for neural networks that produce high accuracy and low energy consumption. We discuss the vali…
Bounding the List Color Function Threshold from Above
Hemanshu Kaul, Akash Kumar, Andrew Liu +5
The chromatic polynomial of a graph , denoted , is equal to the number of proper -colorings of for each . In 1990, Kostochka and Sidorenko intro…
Approximating Dasgupta Cost in Sublinear Time from a Few Random Seeds
Michael Kapralov, Akash Kumar, Silvio Lattanzi +2
Testing graph cluster structure has been a central object of study in property testing since the foundational work of Goldreich and Ron [STOC'96] on expansion testing, i.e. the pro…
Exact recovery algorithm for Planted Bipartite Graph in Semi-random Graphs
Akash Kumar, Anand Louis, Rameesh Paul
The problem of finding the largest induced balanced bipartite subgraph in a given graph is NP-hard. This problem is closely related to the problem of finding the smallest Odd Cycle…
Video Action Detection: Analysing Limitations and Challenges
Rajat Modi, Aayush Jung Rana, Akash Kumar +4
Beyond possessing large enough size to feed data hungry machines (eg, transformers), what attributes measure the quality of a dataset? Assuming that the definitions of such attribu…
End-to-End Semi-Supervised Learning for Video Action Detection
Akash Kumar, Yogesh Singh Rawat
In this work, we focus on semi-supervised learning for video action detection which utilizes both labeled as well as unlabeled data. We propose a simple end-to-end consistency base…
On the List Color Function Threshold
Hemanshu Kaul, Akash Kumar, Jeffrey A. Mudrock +3
The chromatic polynomial of a graph , denoted , is equal to the number of proper -colorings of . The list color function of graph , denoted , is…
Logic Synthesis Meets Machine Learning: Trading Exactness for Generalization
Shubham Rai, Walter Lau Neto, Yukio Miyasaka +37
Logic synthesis is a fundamental step in hardware design whose goal is to find structural representations of Boolean functions while minimizing delay and area. If the function is c…
SIMDive: Approximate SIMD Soft Multiplier-Divider for FPGAs with Tunable Accuracy
Zahra Ebrahimi, Salim Ullah, Akash Kumar
The ever-increasing quest for data-level parallelism and variable precision in ubiquitous multimedia and Deep Neural Network (DNN) applications has motivated the use of Single Inst…
ExPAN(N)D: Exploring Posits for Efficient Artificial Neural Network Design in FPGA-based Systems
Suresh Nambi, Salim Ullah, Aditya Lohana +3
The recent advances in machine learning, in general, and Artificial Neural Networks (ANN), in particular, has made smart embedded systems an attractive option for a larger number o…
ParaLarH: Parallel FPGA Router based upon Lagrange Heuristics
Rohit Agrawal, Kapil Ahuja, Dhaarna Maheshwari +1
Routing of the nets in Field Programmable Gate Array (FPGA) design flow is one of the most time consuming steps. Although Versatile Place and Route (VPR), which is a commonly used…
Deletion to Induced Matching
Akash Kumar, Mithilesh Kumar
In the DELETION TO INDUCED MATCHING problem, we are given a graph on vertices, edges and a non-negative integer and asks whether there exists a set of vertices $S \…
SeqL: Secure Scan-Locking for IP Protection
Seetal Potluri, Aydin Aysu, Akash Kumar
Existing logic-locking attacks are known to successfully decrypt functionally correct key of a locked combinational circuit. It is possible to extend these attacks to real-world Si…
Detecting Deepfakes with Metric Learning
Akash Kumar, Arnav Bhavsar
With the arrival of several face-swapping applications such as FaceApp, SnapChat, MixBooth, FaceBlender and many more, the authenticity of digital media content is hanging on a ver…
Syn2Real: Forgery Classification via Unsupervised Domain Adaptation
Akash Kumar, Arnav Bhavasar
In recent years, image manipulation is becoming increasingly more accessible, yielding more natural-looking images, owing to the modern tools in image processing and computer visio…
Copy-Move Forgery Classification via Unsupervised Domain Adaptation
Akash Kumar, Arnav Bhavsar
In the current era, image manipulation is becoming increasingly easier, yielding more natural looking images, owing to the modern tools in image processing and computer vision tech…