An efficient network on-chip architecture based on isolating local and non-local communications. - Vahideh Akhlaghi; Mehdi Kamal; Ali Afzali-Kusha; Massoud Pedram (Comput. Electr. Eng., 2015)

Resistive Bloom filters: From approximate membership to approximate computing with bounded errors. - Vahideh Akhlaghi; Abbas Rahimi; Rajesh K. Gupta 001 (DATE, 2016)

Quiver: Using Control Perturbations to Increase the Observability of Sensor Data in Smart Buildings. - Jason Koh; Bharathan Balaji; Vahideh Akhlaghi; Yuvraj Agarwal; Rajesh Gupta 001 (CoRR, 2016)

LEMAX: learning-based energy consumption minimization in approximate computing with quality guarantee. - Vahideh Akhlaghi; Sicun Gao; Rajesh K. Gupta 001 (DAC, 2018)

Energy-efficient neural networks using approximate computation reuse. - Xun Jiao; Vahideh Akhlaghi; Yu Jiang 001; Rajesh K. Gupta 001 (DATE, 2018)

SnaPEA: Predictive Early Activation for Reducing Computation in Deep Convolutional Neural Networks. - Vahideh Akhlaghi; Amir Yazdanbakhsh; Kambiz Samadi; Rajesh K. Gupta 001; Hadi Esmaeilzadeh (ISCA, 2018)

Accelerating Local Binary Pattern Networks with Software-Programmable FPGAs. - Jeng-Hau Lin; Atieh Lotfi; Vahideh Akhlaghi; Zhuowen Tu; Rajesh K. Gupta 001 (DATE, 2019)

Associative Convolutional Layers. - Hamed Omidvar; Vahideh Akhlaghi; Massimo Franceschetti; Rajesh K. Gupta 001 (CoRR, 2019)

Algorithm-Hardware Optimization of Deep Neural Networks for Edge Applications. - Vahideh Akhlaghi (2020)

Associative Convolutional Layers. - Hamed Omidvar; Vahideh Akhlaghi; Hao Su; Massimo Franceschetti; Rajesh K. Gupta 001 (AISTATS, 2021)