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P-NP | 2 years ago
B: Priority disputes with Dr. Bengio (original date v Bengio's date): B1: Generative adversarial networks or GANs (1990 v 2014) B2: Vanishing gradient problem (1991 v 1994) B3: Metalearning (1987 v 1991) B4: Learning soft attention (1991-93 v 2014) for Transformers etc. B5: Gated recurrent units (2000 v 2014) B6: Auto-regressive neural nets for density estimation (1995 v 1999) B7: Time scale hierarchy in neural nets (1991 v 1995)
H: Priority disputes with Dr. Hinton (original date v Hinton's date): H1: Unsupervised/self-supervised pre-training for deep learning (1991 v 2006) H2: Distilling one neural net into another neural net (1991 v 2015) H3: Learning sequential attention with neural nets (1990 v 2010) H4: NNs program NNs: fast weight programmers (1991 v 2016) and linear Transformers H5: Speech recognition through deep learning (2007 v 2012) H6: Biologically plausible forward-only deep learning (1989, 1990, 2021 v 2022)
L: Priority disputes with Dr. LeCun (original date v LeCun's date): L1: Differentiable architectures / intrinsic motivation (1990 v 2022) L2: Multiple levels of abstraction and time scales (1990-91 v 2022) L3: Informative yet predictable representations (1997 v 2022) L4: Learning to act largely by observation (2015 v 2022)
P-NP|2 years ago
I think there is a reason why the ACM Turing awardees have never tried to defend themselves by presenting facts to the contrary: because they can't.
This might get interesting:
> The "Policy for Honors Conferred by ACM"[ACM23] mentions that ACM "retains the right to revoke an Honor previously granted if ACM determines that it is in the best interests of the field to do so." So I ask ACM to evaluate the presented evidence and decide about further actions.